335 results on '"Ezhov, M."'
Search Results
152. [The distribution of the mosquitoes of the Anopheles maculipennis complex (Diptera, Culicidae, Anophelinae) in Central Asia]
- Author
-
Zvantsov, A. B., Mikhail Gordeev, Goriacheva, I. I., and Ezhov, M. N.
153. Genetic analysis of malaria mosquitoes of Anopheles maculipennis (Diptera, Culicidae) complex from Armenia
- Author
-
Keshish Ian, A., Mikhail Gordeev, Bezzhonova, O. V., Goriacheva, I. I., Zvantsov, A. B., Davidiants, V. A., and Ezhov, M. N.
154. High Level of Lipoprotein (a) as a Predictor of Poor Long-Term Prognosis After Coronary Artery Bypass Surgery
- Author
-
Ezhov, M. V., Safarova, M. S., Olga Afanasieva, Il Ina, L. N., Lyakishev, A. A., and Pokrovsky, S. N.
155. Effect of therapy with rosuvastatin on lipid spectrum, factors of inflammation and endothelial function in patients with ischemic heart disease
- Author
-
Igor Sergienko, Samoilenko, E. Yu, Masenko, V. P., Ezhov, M. V., Sumarokov, A. B., Tkachev, G. A., Pogorelova, O. A., Balakhonova, T. V., and Naumov, V. G.
156. Effect of statin therapy on dynamics of vascular endothelial growth factor and fibroblast growth factor in patients with ischemic heart disease
- Author
-
Igor Sergienko, Semenova, A. E., Masenko, V. P., Ezhov, M. V., Gabrusenko, S. A., Kukharchuk, V. V., and Belenkov, I. N.
157. Normative values for carotid intima media thickness and its progression: Are they transferrable outside of their cohort of origin?
- Author
-
Liao X, Gd, Norata, Jf, Polak, Cd, Stehouwer, Catapano A, Rundek T, Ezhov M, Sander D, Sg, Thompson, Mw, Lorenz, Prog-Imt, Study Group, Balakhonova T, Maya Safarova, Grigore L, Jp, Empana, Hj, Lin, McLachlan S, Bokemark L, Ronkainen K, and Schminke U
158. T05-P-001 C-Reactive protein in stable coronaryheart disease patients
- Author
-
Ezhov, M., Sumarokov, A., Kambegova, A., Raimbekova, I., Masenko, V., and Naumov, V.
- Published
- 2005
- Full Text
- View/download PDF
159. Global perspective of familial hypercholesterolaemia: a cross-sectional study from the EAS Familial Hypercholesterolaemia Studies Collaboration (FHSC)
- Author
-
Jie Lin, Snejana Tisheva, Ishwar C. Verma, Francesco Cipollone, Liam R. Brunham, Florentina Predica, Perla A.C. Gonzalez, Jocelyne Inamo, André R. Miserez, Belma Pojskic, Michel Farnier, Avishay Ellis, Katia Bonomo, Ibrahim Al-Zakwani, Maria Grazia Zenti, Humberto A. Lopez, Khairul Shafiq Ibrahim, Erkin M. Mirrakhimov, Alexey Meshkov, Jose P. de Moura, Muthukkaruppan Annamalai, Raul D. Santos, F. Paillard, Maria Del Ben, Jan Lacko, Miguel T. Rico, Ximena Reyes, Laura E.G. de Leon, Noor Shafina Mohd Nor, Ulrich Julius, Mohammed A. Batais, Dieter Böhm, Ta-Chen Su, Takuya Kobayashi, Magdalena Chmara, Marco Gebauer, Marcos M. Lima-Martínez, Ravshanbek D. Kurbanov, Daisaku Masuda, Amro El-Hadidy, Melanie Schüler, Francisco Fuentes, Florian J. Mayer, Helena Vaverkova, F. Ulrich Beil, Juraj Bujdak, Mario Stoll, Isabelle Ruel, Elena Dorn, Thomas M. Stulnig, Abubaker Elfatih, Rano B. Alieva, Jiri Vesely, Valérie Carreau, Cristina M. Sibaja, Sophie Béliard, Olivier Ziegler, Adriana Branchi, Daniel Schurr, G.B. John Mancini, Tai E. Shyong, Eric L.T. Siang, Mafalda Bourbon, Zerrin Yigit, Meral Kayıkçıoğlu, Jacques Genest, Wei Yu, Michal Vrablík, Shavkat U. Hoshimov, Dan Gaita, Antonio Pipolo, Ashraf H.A. AlQudaimi, Walter Speidl, Gianfranco Parati, Zaliha Ismail, Victoria M. Zubieta, René Valéro, Tomas Salek, Hana Halamkova, Gustavs Latkovskis, Nicole Allendorf-Ostwald, Agnes Perrin, Vladimir Soska, Anastasia Garoufi, Francisco Araujo, Nacu C. Portilla, Thomas Segiet, Charalambos Koumaras, Hila Knobler, Fatih Sivri, Hani Altaradi, Ivan Pećin, Long Jiang, Alexander Dressel, Marlena Woś, Jana Franekova, D. Agapakis, Quitéria Rato, Dirk J. Blom, Marcin A. Bartlomiejczyk, Krzysztof Dyrbuś, Maurizio Averna, Phivos Symeonides, Yung A. Chua, Asim Rana, András Nagy, Juan C.G. Cuellar, Alexander Jäkel, Maya Safarova, Neama Luqman, Amalia-Despoina Koutsogianni, Patrick Tounian, Jose A. Alvarez, Ada Cuevas, Corinna Richter, Sybil Charrieres, Vitaliy Zafiraki, Michalis Doumas, Angela Lux, Thanh Huong Truong, Elaine Chow, José Luis Díaz-Díaz, Jesus R.H. Almada, Sabine Füllgraf-Horst, Gustavo G. Retana, Claudio Borghi, Gianni Biolo, Ivajlo Tzvetkov, Patrícia Pais, Mehmet Akbulut, Kumiko Nagahama, Oner Ozdogan, Frank Leistikow, Jianxun He, Alexander R.M. Lyons, Poranee Ganokroj, Luis E.S. Mendia, Ann-Cathrin Koschker, Gabriela A.G. Ramirez, Dainus Gilis, Karin Balinth, José Ramiro Cruz, Paolo Calabrò, Alberico L. Catapano, Emmanouil Skalidis, Hamida Al-Barwani, Genovefa Kolovou, Carolyn S.P. Lam, Yoto Yotov, Yaacov Henkin, Gabriella Iannuzzo, Aimi Z. Razman, Alma B.M. Rodriguez, Hans Dieplinger, Darlington E. Obaseki, Ursulo J. Herrera, Arcangelo Iannuzzi, Christoph Säly, Elena Olmastroni, Francisco G. Padilla, S.A. Nazli, Ioanna Gouni-Berthold, Miriam Kozárová, Urh Groselj, Igor Shaposhnik, Lorenzo Iughetti, Nawal Rwaili, Cinthia E. Jannes, Andrea Bartuli, Mikhail Voevoda, Marat V. Ezhov, Yanyu Duan, Alper Sonmez, Mustafa Yenercag, Ariane Sultan, Natasza Gilis-Malinowska, Tavintharan Subramaniam, Mohamed Ashraf, Jing Pang, Kota Matsuki, Tao Jiang, Gerald Klose, Eduardo A.R. Rodriguez, Lucie Solcova, Riccardo Sarzani, Mahmoud Traina, Alejandra Vázquez Cárdenas, Gordon A. Francis, Adolat V. Ziyaeva, Ronen Durst, Maciej Banach, Francisco Silva, Heribert Schunkert, Børge G. Nordestgaard, Ziyou Liu, Ahmad Bakhtiar Md Radzi, Hana Rosolova, Andrea Bäßler, Abdulhalim Jamal Kinsara, Noël Peretti, Victor Gurevich, Margarita T. Tamayo, Abdullah Tuncez, Florian Höllerl, Ljubica Stosic, Jianguang Qi, Anja Kirschbaum, Jitendra P.S. Sawhney, Michael Scholl, Kausik K. Ray, Mohamed Bendary, Hapizah Nawawi, Adrienne Tarr, Barbora Nussbaumerova, B.C. Brice, Kurt Huber, Noor Alicezah Mohd Kasim, A. Rahman A. Jamal, Vaclava Palanova, Giacomo Biasucci, Pucong Ye, Eva Cubova, Roopa Mehta, Rüdiger Schweizer, Veronica Zampoleri, Jacek Jóźwiak, Alyaa Al-Khateeb, Jing Hong, Katarina Raslova, Kirsten B. Holven, Tatiana Rozkova, Reinhold Busch, Alexander Klabnik, Konrad Hein, Eloy A.Z. Carrillo, Robin Urbanek, Livia Pisciotta, Fatma Y. Coskun, Jose J.G. Garcia, Valerio Pecchioli, Azra D. Nalbantic, Weerapan Khovidhunkit, Jernej Kovac, Michaela Kadurova, Mohammed Al-Jarallah, Vita Saripo, Christos V. Rizos, Jie Peng, Ang L. Chua, Dorothee Deiss, Nor A.A. Murad, Aneta Stróżyk, See Kwok, Gökhan Alici, Gillian J. Pilcher, John J.P. Kastelein, Dmitry Duplyakov, Calin Lengher, Milena Budikova, C. Azzopardi, Christina Antza, Luis E.V. Arroyo, Khalid Al-Jumaily, Ahmad Al-Sarraf, Carlos A. Aguilar-Salinas, Erkayim Bektasheva, Arta Upena-RozeMicena, Qian Wang, Xumin Wang, Leah Leavit, Radzi Rahmat, Selim Topcu, Željko Reiner, Lorenzo Maroni, Matija Cevc, Elizabeth R. Cooremans, Masatsune Ogura, Tevfik Sabuncu, Ruy D Arjona Villicaña, Andrea Giaccari, Xuesong Fan, Auryan Szalat, Sanjaya Dissanayake, Etienne Khoury, Anja Vogt, Hermann Toplak, Alexis Baass, Isabel Palma, Gaelle Sablon, Dana A. Hay, Ya Yang, Margus Viigimaa, Erik S.G. Stroes, Dror Harats, Konstantin Krychtiuk, Zesen Liu, Aleksandra Parczewska, Yves Cottin, Yichen Qu, Mathilde Di-Fillipo, Agnieszka Konopka, Lamija Pojskic, Guadalupe J. Dominguez, Ahmet Temizhan, Roberto C. Chacon, Ibrahim E. Dural, Qiang Yong, G. Kees Hovingh, Kang Meng, Sandra Kutkiene, Julie Lemale, Reinhold Innerhofer, Alexandros D. Tselepis, Handrean Soran, Wolfgang König, Bassam Atallah, Olena Mitchenko, Jana Cepova, Eduardo M. Rodriguez, Ulrich Laufs, Norhidayah Rosman, Alena Lubasova, V. Durlach, Frederick J. Raal, Elyor Khodzhiboboev, Cristina Pederiva, Hui Yuan, Ashraf Reda, Fahad Alnouri, Konstantinos Tziomalos, Thanh T. Le, Jana Sirotiakova, Régis Hankard, Hector E.A. Cazares, Betsabel Rodriguez, Lenka Pavlickova, Assen Goudev, Julius Katzmann, Diana Boger, Wael Almahmeed, Katarina T. Podkrajsek, Sabina Zambon, Fahri Bayram, Nadia Citroni, Samir Rafla, Vincent Rigalleau, Aleksandr B. Shek, Hani Sabbour, Berenice G. Guzman, Shoshi Shpitzen, Eric Tarantino, Ahmed Bendary, Fedya Nikolov, Jean Bergeron, Stefan Kopf, Iva Rasulic, Gerald F. Watts, Muhammad I.A. Hafidz, Mehmet B. Yilmaz, Kathrin Biolik, Ira A. Haack, Robert A. Hegele, Sonia Dulong, Bartosz Wasąg, Osama Sanad, Susana Correia, Zhenjia Wang, Dana Biedermann, Christel König, Helena Podzimkova, Ihab Daoud, Mohammad Alghamdi, Dražen Perica, László Márk, Iosif Koutagiar, Volkan Dogan, Vladimir Blaha, Chandrashekhar K. Ponde, Katerina Valoskova, Amer A. Jabbar, Azhari Rosman, Sazzli Kasim, Mesut Demir, Ulugbek I. Nizamov, Aldo Ferreira-Hermosillo, Dilek Yesilbursa, Atef Elbahry, Arshad Abdulrasheed, Omer A. Elamin, Vasileios Athyros, Joanna Lewek, Gergely Nagy, Ursula Kassner, Jian Jiao, Klaus G. Parhofer, Charlotte Nzeyimana, Marcin Pajkowski, Stanislav Zemek, Jose J.C. Macías, Cornelius Müller, G. Sfikas, Leopoldo Pérez de Isla, Yulia Ragino, Fahad Al-Zadjali, Abdul Rais Sanusi, Anna Rita Roscini, Jean Ferrières, Selim Jambart, Jean Pierre Rabes, Laura Schreier, Hofit Cohen, Olivier S. Descamps, N. Lalic, Christine Stumpp, Antonio J. Vallejo-Vaz, Jutta Christmann, Manuela Casula, Mariko Harada-Shiba, Olga Lunegova, Ewa Starostecka, Nicolas D. Oca, Alain Carrié, Achilleas Attilakos, Savas Ozer, Andreea Dumitrescu, Jürgen Merke, Urte Aliosaitiene, Evangelos Liberopoulos, Manuel O. De los Rios Ibarra, Maria J. Virtuoso, Alessandro Lupi, Panagiotis Anagnostis, Ruth Agar, Dorota Ferrieres, George Liamis, José Eduardo Krieger, Mariann Harangi, Fouzia Sadiq, Francois Schiele, Saif Kamal, Mária Audikovszky, Peter Baumgartner, Marta Gazzotti, Daniel Gaudet, Ashanty F. Ortega, Marcin Gruchała, Philippe Moulin, Ljiljana Popovic, Luca Bonanni, E. Kiouri, Mika Hori, Chiara Trenti, Elena Repetti, Carlo Sabbà, Sophie Bernard, Alejandro R. Zazueta, Mirac Vural, Jesus R. Gonzalez, C. Stevens, Francesca Carubbi, Wenhui Wen, Sabri Demircan, Kanika I. Dharmayat, Anne Tybjærg-Hansen, Elizabete Terauda, Claudia Zemmrich, Alphonsus Isara, Fabiola L. Sobrevilla, Anell Hernandez Garcia, Ibrahim Sisic, Justin T. I-Shing, Yvonne Winhofer-Stöckl, Luya Wang, Manfred Mayer, Mohanad Al-ageedi, Judith Wiener, Mohammed Al-Kindi, Anis Safura Ramli, Yan Chen, Denis Angoulvant, Aytekin Oguz, K.H. Wolmarans, Claudio Ferri, Tomáš Freiberger, Lubomira Cermakova, Julieta D.M. Portano, Pierre Henri Ducluzeau, Katerina Vonaskova, Levent H. Can, Mario H.F. Andrade, György Paragh, C. Ebenbichler, Karina J.A. Rivera, Alia Khudari, Elisabeth Steinhagen-Thiessen, Ana C. Alves, Victoria Korneva, Sandra Singh, Georgia Anastasiou, Nur S. Hamzan, Massimo Federici, Lale Tokgozoglu, Hector G. Alcala, Oana Moldovan, Giuseppe Mandraffino, Swarup A.V. Shah, Lukas Burda, Ersel Onrat, Manuel de los Reyes Barrera Bustillo, Mirjana Radovic, Arman Postadzhiyan, Nien-Tzu Chang, Aylin Yildirir, Martin Mäser, Bruno Fink, Svetlana Mosteoru, Ulrike Schatz, Luis A.V. Talavera, Magdalena Dusejovska, Richard Ceska, Faisal A. Al-Allaf, T.F. Ashavaid, Gereon Böll, Sona Machacova, Gonzalo C. Vargas, Antonio Gallo, Elina Pantchechnikova, Lukas Tichy, Gersina Rega-Kaun, Moses Elisaf, Branislav Vohnout, Antonio Bossi, Suad Al-Mukhaini, Natasa Rajkovic, Ursa Sustar, Merih Kutlu, Mohamed Sobhy, Britta Otte, Ana M. Medeiros, Borut Jug, Patrick Couture, Rodrigo Alonso, Wolfgang Seeger, Guzal J. Abdullaeva, Ahmet Celik, Nasreen Al-Sayed, Béla Benczúr, Petra E. Khoury, Rafezah Razali, Ma L.R. Osorio, Ruiying Zhang, Monica M.N. Usme, Humberto Garcia Aguilar, Ceyhun Ceyhan, Antje Spens, Christoph J. Binder, Volker Schrader, Terrance C.S. Jin, Neftali E.A. Villa, Aleksandra Michalska-Grzonkowska, Francesco Purrello, Marshima M. Rosli, Vincent Maher, Dilshad Rasul, Ines Colaço, Ornella Guardamagna, Giuliana Mombelli, Khalid F. AlHabib, Fahmi Alkaf, Marianne Benn, Youmna Ghaleb, Arsenio V. Vazquez, Lakshmi L. Reddy, Salih Kilic, Siti Hamimah Sheikh Abdul Kadir, E. Bilianou, Rossella Marcucci, Sandro Muntoni, Kurt Widhalm, Evangelos A. Zacharis, Kuznetsova T. Yu, Eric Bruckert, Antonia Sonntag, Katerina Rehouskova, Josè Pablo Werba, Leobardo Sauque-Reyna, Myra Tilney, Dov Gavishv, A.M. Fiorenza, Zdenka Krejsova, Hong A. Le, Andrey V. Susekov, Isabel Klein, Mai N.T. Nguyen, Andrejs Erglis, Muge Ildizli, Diane Brisson, Salmi Razali, Winfried März, Ovidio Muñiz-Grijalvo, Justyna Borowiec-Wolna, Ingrid Buganova, Ngoc T. Kim, Yue Wu, István Reiber, Jose C.A. Martinez, Pavel Malina, Sandy Elbitar, Stephan Matthias, Ali F. Abdalsahib, Zlatko Fras, Wilson E Sadoh, Lucas Kleemann, Tayfun Sahin, Martin P. Bogsrud, Fabio Pellegatta, Mohamed A. Shafy, Yuntao Li, Martine Paquette, Zuhier Awan, Arturo Pujia, Xiantao Song, Renata Cifkova, Alexandre C. Pereira, Ioannis Skoumas, Roman Cibulka, Tadej Battelino, Mariusz Gąsior, Ghada Kazamel, Lahore S.U. Shah, Eran Leitersdorf, Niki Katsiki, Daniel Elías-López, Khalid Al-Rasadi, Grete Talviste, Sarka Mala, Rocio M. Alvarado, Pavel Kraml, Gerret Paulsen, Angelina Passaro, Zsolt Karányi, Carine Ayoub, Vera Adamkova, Ivo Petrov, Turky H. Almigbal, Rohana Abdul Ghani, Franck Boccara, Brian W. McCrindle, François Martin, Jamshed J. Dalal, Shitong Cheng, Khalid Al-Waili, Chaoyi Zhang, Ramon M. Prado, Lubica Cibickova, Lubomira Fabryova, Tobias Wiesner, Thuhairah Hasrah Abdul Rahman, Tan J. Le, Marcello Arca, Sabine Scholl-Bürgi, Juan R. Saucedo, Georgijs Nesterovics, Carla V.M. Valencia, Alexander Stadelmann, Vasileios Kotsis, Lina Badimon, Shizuya Yamashita, Jose C.M. Oyervides, Lay K. Teh, Susanne Greber-Platzer, Marianne Abifadel, Ruta Meiere, Wibke Reinhard, Pablo Corral, Nina Schmidt, Alain Pradignac, A. David Marais, Marta Jordanova, Marzena Romanowska-Kocejko, Johannes Scholl, Brian Tomlinson, Laura G.G. Herrera, Loukianos S. Rallidis, Pedro Mata, Sameh Emil, Matej Mlinaric, Emile Ferrari, Suraya Abdul Razak, Alexandra Ershova, Andrie G. Panayiotou, Alinna Y.R. Garcia, Kairat Davletov, Katarina Lalic, Doan L. Do, Krzysztof Chlebus, Ricardo A. Carrera, Daniel I.P. Vazquez, Nikolaos Sakkas, Liyuan Xu, Mays Altaey, Aysa Hacioglu, Alexandro J. Martagon, Marta Żarczyńska-Buchowiecka, Michael Schömig, Jürgen Homberger, Andrea Benso, Bertrand Cariou, Ardon Rubinstein, Omer Gedikli, Emre Durakoglugil, Mei Chong, Bahadir Kirilmaz, Suhaila Abd Muid, Jose M. Salgado, Berenice P. Aparicio, Mutaz Alkhnifsawi, Bruno Vergès, Cécile Yelnik, Goreti Lobarinhas, Zaneta Petrulioniene, Sylvia Asenjo, Aytul B. Yildirim, László Bajnok, Vallejo-Vaz A.J., Stevens C.A.T., Lyons A.R.M., Dharmayat K.I., Freiberger T., Hovingh G.K., Mata P., Raal F.J., Santos R.D., Soran H., Watts G.F., Abifadel M., Aguilar-Salinas C.A., Alhabib K.F., Alkhnifsawi M., Almahmeed W., Alnouri F., Alonso R., Al-Rasadi K., Al-Sarraf A., Al-Sayed N., Araujo F., Ashavaid T.F., Banach M., Beliard S., Benn M., Binder C.J., Bogsrud M.P., Bourbon M., Chlebus K., Corral P., Davletov K., Descamps O.S., Durst R., Ezhov M., Gaita D., Genest J., Groselj U., Harada-Shiba M., Holven K.B., Kayikcioglu M., Khovidhunkit W., Lalic K., Latkovskis G., Laufs U., Liberopoulos E., Lima-Martinez M.M., Lin J., Maher V., Marais A.D., Marz W., Mirrakhimov E., Miserez A.R., Mitchenko O., Nawawi H., Nordestgaard B.G., Panayiotou A.G., Paragh G., Petrulioniene Z., Pojskic B., Postadzhiyan A., Raslova K., Reda A., Reiner, Sadiq F., Sadoh W.E., Schunkert H., Shek A.B., Stoll M., Stroes E., Su T.-C., Subramaniam T., Susekov A.V., Tilney M., Tomlinson B., Truong T.H., Tselepis A.D., Tybjaerg-Hansen A., Vazquez Cardenas A., Viigimaa M., Wang L., Yamashita S., Kastelein J.J.P., Bruckert E., Vohnout B., Schreier L., Pang J., Ebenbichler C., Dieplinger H., Innerhofer R., Winhofer-Stockl Y., Greber-Platzer S., Krychtiuk K., Speidl W., Toplak H., Widhalm K., Stulnig T., Huber K., Hollerl F., Rega-Kaun G., Kleemann L., Maser M., Scholl-Burgi S., Saly C., Mayer F.J., Sablon G., Tarantino E., Nzeyimana C., Pojskic L., Sisic I., Nalbantic A.D., Jannes C.E., Pereira A.C., Krieger J.E., Petrov I., Goudev A., Nikolov F., Tisheva S., Yotov Y., Tzvetkov I., Baass A., Bergeron J., Bernard S., Brisson D., Brunham L.R., Cermakova L., Couture P., Francis G.A., Gaudet D., Hegele R.A., Khoury E., Mancini G.B.J., McCrindle B.W., Paquette M., Ruel I., Cuevas A., Asenjo S., Wang X., Meng K., Song X., Yong Q., Jiang T., Liu Z., Duan Y., Hong J., Ye P., Chen Y., Qi J., Li Y., Zhang C., Peng J., Yang Y., Yu W., Wang Q., Yuan H., Cheng S., Jiang L., Chong M., Jiao J., Wu Y., Wen W., Xu L., Zhang R., Qu Y., He J., Fan X., Wang Z., Chow E., Pecin I., Perica D., Symeonides P., Vrablik M., Ceska R., Soska V., Tichy L., Adamkova V., Franekova J., Cifkova R., Kraml P., Vonaskova K., Cepova J., Dusejovska M., Pavlickova L., Blaha V., Rosolova H., Nussbaumerova B., Cibulka R., Vaverkova H., Cibickova L., Krejsova Z., Rehouskova K., Malina P., Budikova M., Palanova V., Solcova L., Lubasova A., Podzimkova H., Bujdak J., Vesely J., Jordanova M., Salek T., Urbanek R., Zemek S., Lacko J., Halamkova H., Machacova S., Mala S., Cubova E., Valoskova K., Burda L., Bendary A., Daoud I., Emil S., Elbahry A., Rafla S., Sanad O., Kazamel G., Ashraf M., Sobhy M., El-Hadidy A., Shafy M.A., Kamal S., Bendary M., Talviste G., Angoulvant D., Boccara F., Cariou B., Carreau V., Carrie A., Charrieres S., Cottin Y., Di-Fillipo M., Ducluzeau P.H., Dulong S., Durlach V., Farnier M., Ferrari E., Ferrieres D., Ferrieres J., Gallo A., hankard R., Inamo J., Lemale J., Moulin P., Paillard F., Peretti N., Perrin A., Pradignac A., Rabes J.P., Rigalleau V., Sultan A., Schiele F., Tounian P., Valero R., Verges B., Yelnik C., Ziegler O., Haack I.A., Schmidt N., Dressel A., Klein I., Christmann J., Sonntag A., Stumpp C., Boger D., Biedermann D., Usme M.M.N., Beil F.U., Klose G., Konig C., Gouni-Berthold I., Otte B., Boll G., Kirschbaum A., Merke J., Scholl J., Segiet T., Gebauer M., Predica F., Mayer M., Leistikow F., Fullgraf-Horst S., Muller C., Schuler M., Wiener J., Hein K., Baumgartner P., Kopf S., Busch R., Schomig M., Matthias S., Allendorf-Ostwald N., Fink B., Bohm D., Jakel A., Koschker A.-C., Schweizer R., Vogt A., Parhofer K., Konig W., Reinhard W., Bassler A., Stadelmann A., Schrader V., Katzmann J., Tarr A., Steinhagen-Thiessen E., Kassner U., Paulsen G., Homberger J., Zemmrich C., Seeger W., Biolik K., Deiss D., Richter C., Pantchechnikova E., Dorn E., Schatz U., Julius U., Spens A., Wiesner T., Scholl M., Rizos C.V., Sakkas N., Elisaf M., Skoumas I., Tziomalos K., Rallidis L., Kotsis V., Doumas M., Athyros V., Skalidis E., Kolovou G., Garoufi A., Bilianou E., Koutagiar I., Agapakis D., Kiouri E., Antza C., Katsiki N., Zacharis E., Attilakos A., Sfikas G., Koumaras C., Anagnostis P., Anastasiou G., Liamis G., Koutsogianni A.-D., Karanyi Z., Harangi M., Bajnok L., Audikovszky M., Mark L., Benczur B., Reiber I., Nagy G., Nagy A., Reddy L.L., Shah S.A.V., Ponde C.K., Dalal J.J., Sawhney J.P.S., Verma I.C., Altaey M., Al-Jumaily K., Rasul D., Abdalsahib A.F., Jabbar A.A., Al-ageedi M., Agar R., Cohen H., Ellis A., Gavishv D., Harats D., Henkin Y., Knobler H., Leavit L., Leitersdorf E., Rubinstein A., Schurr D., Shpitzen S., Szalat A., Casula M., Zampoleri V., Gazzotti M., Olmastroni E., Sarzani R., Ferri C., Repetti E., Sabba C., Bossi A.C., Borghi C., Muntoni S., Cipollone F., Purrello F., Pujia A., Passaro A., Marcucci R., Pecchioli V., Pisciotta L., Mandraffino G., Pellegatta F., Mombelli G., Branchi A., Fiorenza A.M., Pederiva C., Werba J.P., Parati G., Carubbi F., Iughetti L., Iannuzzi A., Iannuzzo G., Calabro P., Averna M, Biasucci G., Zambon S., Roscini A.R., Trenti C., Arca M., Federici M., Del Ben M., Bartuli A., Giaccari A., Pipolo A., Citroni N., Guardamagna O., Bonomo K., Benso A., Biolo G., Maroni L., Lupi A., Bonanni L., Zenti M.G., Matsuki K., Hori M., Ogura M., Masuda D., Kobayashi T., Nagahama K., Al-Jarallah M., Radovic M., Lunegova O., Bektasheva E., Khodzhiboboev E., Erglis A., Gilis D., Nesterovics G., Saripo V., Meiere R., Upena-RozeMicena A., Terauda E., Jambart S., Khoury P.E., Elbitar S., Ayoub C., Ghaleb Y., Aliosaitiene U., Kutkiene S., Kasim N.A.M., Nor N.S.M., Ramli A.S., Razak S.A., Al-Khateeb A., Kadir S.H.S.A., Muid S.A., Rahman T.A., Kasim S.S., Radzi A.B.M., Ibrahim K.S., Razali S., Ismail Z., Ghani R.A., Hafidz M.I.A., Chua A.L., Rosli M.M., Annamalai M., Teh L.K., Razali R., Chua Y.A., Rosman A., Sanusi A.R., Murad N.A.A., Jamal A.R.A., Nazli S.A., Razman A.Z., Rosman N., Rahmat R., Hamzan N.S., Azzopardi C., Mehta R., Martagon A.J., Ramirez G.A.G., Villa N.E.A., Vazquez A.V., Elias-Lopez D., Retana G.G., Rodriguez B., Macias J.J.C., Zazueta A.R., Alvarado R.M., Portano J.D.M., Lopez H.A., Sauque-Reyna L., Herrera L.G.G., Mendia L.E.S., Aguilar H.G., Cooremans E.R., Aparicio B.P., Zubieta V.M., Gonzalez P.A.C., Ferreira-Hermosillo A., Portilla N.C., Dominguez G.J., Garcia A.Y.R., Cazares H.E.A., Gonzalez J.R., Valencia C.V.M., Padilla F.G., Prado R.M., De los Rios Ibarra M.O., Villicana R.D.A., Rivera K.J.A., Carrera R.A., Alvarez J.A., Martinez J.C.A., de los Reyes Barrera Bustillo M., Vargas G.C., Chacon R.C., Andrade M.H.F., Ortega A.F., Alcala H.G., de Leon L.E.G., Guzman B.G., Garcia J.J.G., Cuellar J.C.G., Cruz J.R.G., Garcia A.H., Almada J.R.H., Herrera U.J., Sobrevilla F.L., Rodriguez E.M., Sibaja C.M., Rodriguez A.B.M., Oyervides J.C.M., Vazquez D.I.P., Rodriguez E.A.R., Osorio M.L.R., Saucedo J.R., Tamayo M.T., Talavera L.A.V., Arroyo L.E.V., Carrillo E.A.Z., Isara A., Obaseki D.E., Al-Waili K., Al-Zadjali F., Al-Zakwani I., Al-Kindi M., Al-Mukhaini S., Al-Barwani H., Rana A., Shah L.S.U., Starostecka E., Konopka A., Lewek J., Bartlomiejczyk M., Gasior M., Dyrbus K., Jozwiak J., Gruchala M., Pajkowski M., Romanowska-Kocejko M., Zarczynska-Buchowiecka M., Chmara M., Wasag B., Parczewska A., Gilis-Malinowska N., Borowiec-Wolna J., Strozyk A., Wos M., Michalska-Grzonkowska A., Medeiros A.M., Alves A.C., Silva F., Lobarinhas G., Palma I., de Moura J.P., Rico M.T., Rato Q., Pais P., Correia S., Moldovan O., Virtuoso M.J., Salgado J.M., Colaco I., Dumitrescu A., Lengher C., Mosteoru S., Meshkov A., Ershova A., Rozkova T., Korneva V., Yu K.T., Zafiraki V., Voevoda M., Gurevich V., Duplyakov D., Ragino Y., Safarova M., Shaposhnik I., Alkaf F., Khudari A., Rwaili N., Al-Allaf F., Alghamdi M., Batais M.A., Almigbal T.H., Kinsara A., AlQudaimi A.H.A., Awan Z., Elamin O.A., Altaradi H., Rajkovic N., Popovic L., Singh S., Stosic L., Rasulic I., Lalic N.M., Lam C., Le T.J., Siang E.L.T., Dissanayake S., I-Shing J.T., Shyong T.E., Jin T.C.S., Balinth K., Buganova I., Fabryova L., Kadurova M., Klabnik A., Kozarova M., Sirotiakova J., Battelino T., Kovac J., Mlinaric M., Sustar U., Podkrajsek K.T., Fras Z., Jug B., Cevc M., Pilcher G.J., Blom D.J., Wolmarans K.H., Brice B.C., Muniz-Grijalvo O., Diaz-Diaz J.L., de Isla L.P., Fuentes F., Badimon L., Martin F., Lux A., Chang N.-T., Ganokroj P., Akbulut M., Alici G., Bayram F., Can L.H., Celik A., Ceyhan C., Coskun F.Y., Demir M., Demircan S., Dogan V., Durakoglugil E., Dural I.E., Gedikli O., Hacioglu A., Ildizli M., Kilic S., Kirilmaz B., Kutlu M., Oguz A., Ozdogan O., Onrat E., Ozer S., Sabuncu T., Sahin T., Sivri F., Sonmez A., Temizhan A., Topcu S., Tuncez A., Vural M., Yenercag M., Yesilbursa D., Yigit Z., Yildirim A.B., Yildirir A., Yilmaz M.B., Atallah B., Traina M., Sabbour H., Hay D.A., Luqman N., Elfatih A., Abdulrasheed A., Kwok S., Oca N.D., Reyes X., Alieva R.B., Kurbanov R.D., Hoshimov S.U., Nizamov U.I., Ziyaeva A.V., Abdullaeva G.J., Do D.L., Nguyen M.N.T., Kim N.T., Le T.T., Le H.A., Tokgozoglu L., Catapano A.L., Ray K.K., Vallejo-Vaz, A. J., Stevens, C. A. T., Lyons, A. R. M., Dharmayat, K. I., Freiberger, T., Hovingh, G. K., Mata, P., Raal, F. J., Santos, R. D., Soran, H., Watts, G. F., Abifadel, M., Aguilar-Salinas, C. A., Alhabib, K. F., Alkhnifsawi, M., Almahmeed, W., Alnouri, F., Alonso, R., Al-Rasadi, K., Al-Sarraf, A., Al-Sayed, N., Araujo, F., Ashavaid, T. F., Banach, M., Beliard, S., Benn, M., Binder, C. J., Bogsrud, M. P., Bourbon, M., Chlebus, K., Corral, P., Davletov, K., Descamps, O. S., Durst, R., Ezhov, M., Gaita, D., Genest, J., Groselj, U., Harada-Shiba, M., Holven, K. B., Kayikcioglu, M., Khovidhunkit, W., Lalic, K., Latkovskis, G., Laufs, U., Liberopoulos, E., Lima-Martinez, M. M., Lin, J., Maher, V., Marais, A. D., Marz, W., Mirrakhimov, E., Miserez, A. R., Mitchenko, O., Nawawi, H., Nordestgaard, B. G., Panayiotou, A. G., Paragh, G., Petrulioniene, Z., Pojskic, B., Postadzhiyan, A., Raslova, K., Reda, A., Sadiq, F., Sadoh, W. E., Schunkert, H., Shek, A. B., Stoll, M., Stroes, E., Su, T. -C., Subramaniam, T., Susekov, A. V., Tilney, M., Tomlinson, B., Truong, T. H., Tselepis, A. D., Tybjaerg-Hansen, A., Vazquez Cardenas, A., Viigimaa, M., Wang, L., Yamashita, S., Kastelein, J. J. P., Bruckert, E., Vohnout, B., Schreier, L., Pang, J., Ebenbichler, C., Dieplinger, H., Innerhofer, R., Winhofer-Stockl, Y., Greber-Platzer, S., Krychtiuk, K., Speidl, W., Toplak, H., Widhalm, K., Stulnig, T., Huber, K., Hollerl, F., Rega-Kaun, G., Kleemann, L., Maser, M., Scholl-Burgi, S., Saly, C., Mayer, F. J., Sablon, G., Tarantino, E., Nzeyimana, C., Pojskic, L., Sisic, I., Nalbantic, A. D., Jannes, C. E., Pereira, A. C., Krieger, J. E., Petrov, I., Goudev, A., Nikolov, F., Tisheva, S., Yotov, Y., Tzvetkov, I., Baass, A., Bergeron, J., Bernard, S., Brisson, D., Brunham, L. R., Cermakova, L., Couture, P., Francis, G. A., Gaudet, D., Hegele, R. A., Khoury, E., Mancini, G. B. J., Mccrindle, B. W., Paquette, M., Ruel, I., Cuevas, A., Asenjo, S., Wang, X., Meng, K., Song, X., Yong, Q., Jiang, T., Liu, Z., Duan, Y., Hong, J., Ye, P., Chen, Y., Qi, J., Li, Y., Zhang, C., Peng, J., Yang, Y., Yu, W., Wang, Q., Yuan, H., Cheng, S., Jiang, L., Chong, M., Jiao, J., Wu, Y., Wen, W., Xu, L., Zhang, R., Qu, Y., He, J., Fan, X., Wang, Z., Chow, E., Pecin, I., Perica, D., Symeonides, P., Vrablik, M., Ceska, R., Soska, V., Tichy, L., Adamkova, V., Franekova, J., Cifkova, R., Kraml, P., Vonaskova, K., Cepova, J., Dusejovska, M., Pavlickova, L., Blaha, V., Rosolova, H., Nussbaumerova, B., Cibulka, R., Vaverkova, H., Cibickova, L., Krejsova, Z., Rehouskova, K., Malina, P., Budikova, M., Palanova, V., Solcova, L., Lubasova, A., Podzimkova, H., Bujdak, J., Vesely, J., Jordanova, M., Salek, T., Urbanek, R., Zemek, S., Lacko, J., Halamkova, H., Machacova, S., Mala, S., Cubova, E., Valoskova, K., Burda, L., Bendary, A., Daoud, I., Emil, S., Elbahry, A., Rafla, S., Sanad, O., Kazamel, G., Ashraf, M., Sobhy, M., El-Hadidy, A., Shafy, M. A., Kamal, S., Bendary, M., Talviste, G., Angoulvant, D., Boccara, F., Cariou, B., Carreau, V., Carrie, A., Charrieres, S., Cottin, Y., Di-Fillipo, M., Ducluzeau, P. H., Dulong, S., Durlach, V., Farnier, M., Ferrari, E., Ferrieres, D., Ferrieres, J., Gallo, A., Hankard, R., Inamo, J., Lemale, J., Moulin, P., Paillard, F., Peretti, N., Perrin, A., Pradignac, A., Rabes, J. P., Rigalleau, V., Sultan, A., Schiele, F., Tounian, P., Valero, R., Verges, B., Yelnik, C., Ziegler, O., Haack, I. A., Schmidt, N., Dressel, A., Klein, I., Christmann, J., Sonntag, A., Stumpp, C., Boger, D., Biedermann, D., Usme, M. M. N., Beil, F. U., Klose, G., Konig, C., Gouni-Berthold, I., Otte, B., Boll, G., Kirschbaum, A., Merke, J., Scholl, J., Segiet, T., Gebauer, M., Predica, F., Mayer, M., Leistikow, F., Fullgraf-Horst, S., Muller, C., Schuler, M., Wiener, J., Hein, K., Baumgartner, P., Kopf, S., Busch, R., Schomig, M., Matthias, S., Allendorf-Ostwald, N., Fink, B., Bohm, D., Jakel, A., Koschker, A. -C., Schweizer, R., Vogt, A., Parhofer, K., Konig, W., Reinhard, W., Bassler, A., Stadelmann, A., Schrader, V., Katzmann, J., Tarr, A., Steinhagen-Thiessen, E., Kassner, U., Paulsen, G., Homberger, J., Zemmrich, C., Seeger, W., Biolik, K., Deiss, D., Richter, C., Pantchechnikova, E., Dorn, E., Schatz, U., Julius, U., Spens, A., Wiesner, T., Scholl, M., Rizos, C. V., Sakkas, N., Elisaf, M., Skoumas, I., Tziomalos, K., Rallidis, L., Kotsis, V., Doumas, M., Athyros, V., Skalidis, E., Kolovou, G., Garoufi, A., Bilianou, E., Koutagiar, I., Agapakis, D., Kiouri, E., Antza, C., Katsiki, N., Zacharis, E., Attilakos, A., Sfikas, G., Koumaras, C., Anagnostis, P., Anastasiou, G., Liamis, G., Koutsogianni, A. -D., Karanyi, Z., Harangi, M., Bajnok, L., Audikovszky, M., Mark, L., Benczur, B., Reiber, I., Nagy, G., Nagy, A., Reddy, L. L., Shah, S. A. V., Ponde, C. K., Dalal, J. J., Sawhney, J. P. S., Verma, I. C., Altaey, M., Al-Jumaily, K., Rasul, D., Abdalsahib, A. F., Jabbar, A. A., Al-ageedi, M., Agar, R., Cohen, H., Ellis, A., Gavishv, D., Harats, D., Henkin, Y., Knobler, H., Leavit, L., Leitersdorf, E., Rubinstein, A., Schurr, D., Shpitzen, S., Szalat, A., Casula, M., Zampoleri, V., Gazzotti, M., Olmastroni, E., Sarzani, R., Ferri, C., Repetti, E., Sabba, C., Bossi, A. C., Borghi, C., Muntoni, S., Cipollone, F., Purrello, F., Pujia, A., Passaro, A., Marcucci, R., Pecchioli, V., Pisciotta, L., Mandraffino, G., Pellegatta, F., Mombelli, G., Branchi, A., Fiorenza, A. M., Pederiva, C., Werba, J. P., Parati, G., Carubbi, F., Iughetti, L., Iannuzzi, A., Iannuzzo, G., Calabro, P., Averna, M., Biasucci, G., Zambon, S., Roscini, A. R., Trenti, C., Arca, M., Federici, M., Del Ben, M., Bartuli, A., Giaccari, A., Pipolo, A., Citroni, N., Guardamagna, O., Bonomo, K., Benso, A., Biolo, G., Maroni, L., Lupi, A., Bonanni, L., Zenti, M. G., Matsuki, K., Hori, M., Ogura, M., Masuda, D., Kobayashi, T., Nagahama, K., Al-Jarallah, M., Radovic, M., Lunegova, O., Bektasheva, E., Khodzhiboboev, E., Erglis, A., Gilis, D., Nesterovics, G., Saripo, V., Meiere, R., Upena-RozeMicena, A., Terauda, E., Jambart, S., Khoury, P. E., Elbitar, S., Ayoub, C., Ghaleb, Y., Aliosaitiene, U., Kutkiene, S., Kasim, N. A. M., Nor, N. S. M., Ramli, A. S., Razak, S. A., Al-Khateeb, A., Kadir, S. H. S. A., Muid, S. A., Rahman, T. A., Kasim, S. S., Radzi, A. B. M., Ibrahim, K. S., Razali, S., Ismail, Z., Ghani, R. A., Hafidz, M. I. A., Chua, A. L., Rosli, M. M., Annamalai, M., Teh, L. K., Razali, R., Chua, Y. A., Rosman, A., Sanusi, A. R., Murad, N. A. A., Jamal, A. R. A., Nazli, S. A., Razman, A. Z., Rosman, N., Rahmat, R., Hamzan, N. S., Azzopardi, C., Mehta, R., Martagon, A. J., Ramirez, G. A. G., Villa, N. E. A., Vazquez, A. V., Elias-Lopez, D., Retana, G. G., Rodriguez, B., Macias, J. J. C., Zazueta, A. R., Alvarado, R. M., Portano, J. D. M., Lopez, H. A., Sauque-Reyna, L., Herrera, L. G. G., Mendia, L. E. S., Aguilar, H. G., Cooremans, E. R., Aparicio, B. P., Zubieta, V. M., Gonzalez, P. A. C., Ferreira-Hermosillo, A., Portilla, N. C., Dominguez, G. J., Garcia, A. Y. R., Cazares, H. E. A., Gonzalez, J. R., Valencia, C. V. M., Padilla, F. G., Prado, R. M., De los Rios Ibarra, M. O., Villicana, R. D. A., Rivera, K. J. A., Carrera, R. A., Alvarez, J. A., Martinez, J. C. A., de los Reyes Barrera Bustillo, M., Vargas, G. C., Chacon, R. C., Andrade, M. H. F., Ortega, A. F., Alcala, H. G., de Leon, L. E. G., Guzman, B. G., Garcia, J. J. G., Cuellar, J. C. G., Cruz, J. R. G., Garcia, A. H., Almada, J. R. H., Herrera, U. J., Sobrevilla, F. L., Rodriguez, E. M., Sibaja, C. M., Rodriguez, A. B. M., Oyervides, J. C. M., Vazquez, D. I. P., Rodriguez, E. A. R., Osorio, M. L. R., Saucedo, J. R., Tamayo, M. T., Talavera, L. A. V., Arroyo, L. E. V., Carrillo, E. A. Z., Isara, A., Obaseki, D. E., Al-Waili, K., Al-Zadjali, F., Al-Zakwani, I., Al-Kindi, M., Al-Mukhaini, S., Al-Barwani, H., Rana, A., Shah, L. S. U., Starostecka, E., Konopka, A., Lewek, J., Bartlomiejczyk, M., Gasior, M., Dyrbus, K., Jozwiak, J., Gruchala, M., Pajkowski, M., Romanowska-Kocejko, M., Zarczynska-Buchowiecka, M., Chmara, M., Wasag, B., Parczewska, A., Gilis-Malinowska, N., Borowiec-Wolna, J., Strozyk, A., Wos, M., Michalska-Grzonkowska, A., Medeiros, A. M., Alves, A. C., Silva, F., Lobarinhas, G., Palma, I., de Moura, J. P., Rico, M. T., Rato, Q., Pais, P., Correia, S., Moldovan, O., Virtuoso, M. J., Salgado, J. M., Colaco, I., Dumitrescu, A., Lengher, C., Mosteoru, S., Meshkov, A., Ershova, A., Rozkova, T., Korneva, V., Yu, K. T., Zafiraki, V., Voevoda, M., Gurevich, V., Duplyakov, D., Ragino, Y., Safarova, M., Shaposhnik, I., Alkaf, F., Khudari, A., Rwaili, N., Al-Allaf, F., Alghamdi, M., Batais, M. A., Almigbal, T. H., Kinsara, A., Alqudaimi, A. H. A., Awan, Z., Elamin, O. A., Altaradi, H., Rajkovic, N., Popovic, L., Singh, S., Stosic, L., Rasulic, I., Lalic, N. M., Lam, C., Le, T. J., Siang, E. L. T., Dissanayake, S., I-Shing, J. T., Shyong, T. E., Jin, T. C. S., Balinth, K., Buganova, I., Fabryova, L., Kadurova, M., Klabnik, A., Kozarova, M., Sirotiakova, J., Battelino, T., Kovac, J., Mlinaric, M., Sustar, U., Podkrajsek, K. T., Fras, Z., Jug, B., Cevc, M., Pilcher, G. J., Blom, D. J., Wolmarans, K. H., Brice, B. C., Muniz-Grijalvo, O., Diaz-Diaz, J. L., de Isla, L. P., Fuentes, F., Badimon, L., Martin, F., Lux, A., Chang, N. -T., Ganokroj, P., Akbulut, M., Alici, G., Bayram, F., Can, L. H., Celik, A., Ceyhan, C., Coskun, F. Y., Demir, M., Demircan, S., Dogan, V., Durakoglugil, E., Dural, I. E., Gedikli, O., Hacioglu, A., Ildizli, M., Kilic, S., Kirilmaz, B., Kutlu, M., Oguz, A., Ozdogan, O., Onrat, E., Ozer, S., Sabuncu, T., Sahin, T., Sivri, F., Sonmez, A., Temizhan, A., Topcu, S., Tuncez, A., Vural, M., Yenercag, M., Yesilbursa, D., Yigit, Z., Yildirim, A. B., Yildirir, A., Yilmaz, M. B., Atallah, B., Traina, M., Sabbour, H., Hay, D. A., Luqman, N., Elfatih, A., Abdulrasheed, A., Kwok, S., Oca, N. D., Reyes, X., Alieva, R. B., Kurbanov, R. D., Hoshimov, S. U., Nizamov, U. I., Ziyaeva, A. V., Abdullaeva, G. J., Do, D. L., Nguyen, M. N. T., Kim, N. T., Le, T. T., Le, H. A., Tokgozoglu, L., Catapano, A. L., Ray, K. K., and EAS Familial Hypercholesterolaemia Studies Collaboration (FHSC), Borghi C
- Subjects
Male ,Settore MED/09 - Medicina Interna ,Arterial disease ,Cross-sectional study ,Adult population ,Coronary Disease ,Disease ,Global Health ,Medical and Health Sciences ,Doenças Cardio e Cérebro-vasculares ,Anticholesteremic Agent ,Monoclonal ,Prevalence ,Registries ,Familial Hypercholesterolemia ,Humanized ,Stroke ,11 Medical and Health Sciences ,LS2_9 ,Studies Collaboration ,Anticholesteremic Agents ,General Medicine ,Heart Disease Risk Factor ,Middle Aged ,FHSC global registry data ,Europe ,Treatment Outcome ,Lower prevalence ,Guidance ,lipids (amino acids, peptides, and proteins) ,Female ,Proprotein Convertase 9 ,Familial hypercholesterolaemia ,Life Sciences & Biomedicine ,Human ,Adult ,medicine.medical_specialty ,Combination therapy ,FHSC global registry, heterozygous familial hypercholesterolaemia ,Cardiovascular risk factors ,Antibodies, Monoclonal, Humanized ,Insights ,Antibodies ,NO ,Hyperlipoproteinemia Type II ,Clinician ,Medicine, General & Internal ,Internal medicine ,General & Internal Medicine ,Health Sciences ,medicine ,Humans ,EAS Familial Hypercholesterolaemia Studies Collaboration (FHSC) ,Cross-Sectional Studie ,Science & Technology ,Global Perspective ,business.industry ,Cholesterol, LDL ,medicine.disease ,Cross-Sectional Studies ,Heart Disease Risk Factors ,Hydroxymethylglutaryl-CoA Reductase Inhibitor ,Hydroxymethylglutaryl-CoA Reductase Inhibitors ,business - Abstract
Background The European Atherosclerosis Society Familial Hypercholesterolaemia Studies Collaboration (FHSC) global registry provides a platform for the global surveillance of familial hypercholesterolaemia through harmonisation and pooling of multinational data. In this study, we aimed to characterise the adult population with heterozygous familial hypercholesterolaemia and described how it is detected and managed globally. Methods Using FHSC global registry data, we did a cross-sectional assessment of adults (aged 18 years or older) with a clinical or genetic diagnosis of probable or definite heterozygous familial hypercholesterolaemia at the time they were entered into the registries. Data were assessed overall and by WHO regions, sex, and index versus non-index cases. Findings Of the 61 612 individuals in the registry, 42 167 adults (21 999 [53.6%] women) from 56 countries were included in the study. Of these, 31 798 (75.4%) were diagnosed with the Dutch Lipid Clinic Network criteria, and 35 490 (84.2%) were from the WHO region of Europe. Median age of participants at entry in the registry was 46.2 years (IQR 34.3-58.0); median age at diagnosis of familial hypercholesterolaemia was 44.4 years (32.5-56.5), with 40.2% of participants younger than 40 years when diagnosed. Prevalence of cardiovascular risk factors increased progressively with age and varied by WHO region. Prevalence of coronary disease was 17.4% (2.1% for stroke and 5.2% for peripheral artery disease), increasing with concentrations of untreated LDL cholesterol, and was about two times lower in women than in men. Among patients receiving lipid-lowering medications, 16 803 (81.1%) were receiving statins and 3691 (21.2%) were on combination therapy, with greater use of more potent lipid-lowering medication in men than in women. Median LDL cholesterol was 5.43 mmol/L (IQR 4.32-6.72) among patients not taking lipid-lowering medications and 4.23 mmol/L (3.20-5.66) among those taking them. Among patients taking lipid-lowering medications, 2.7% had LDL cholesterol lower than 1.8 mmol/L; the use of combination therapy, particularly with three drugs and with proprotein convertase subtilisin-kexin type 9 inhibitors, was associated with a higher proportion and greater odds of having LDL cholesterol lower than 1.8 mmol/L. Compared with index cases, patients who were non-index cases were younger, with lower LDL cholesterol and lower prevalence of cardiovascular risk factors and cardiovascular diseases (all p, Pfizer Independent Grant for Learning Change [16157823]; Amgen; Merck Sharp Dohme; Sanofi-Aventis; Daiichi Sankyo; Regeneron; National Institute for Health Research (NIHR) Imperial Biomedical Research Centre, UK; NIHR; Czech Ministry of Health [NU20-02-00261]; Canadian Institutes of Health Research; Austrian Heart Foundation; Tyrolean Regional Government; Gulf Heart Association, The EAS FHSC is an academic initiative that has received funding from a Pfizer Independent Grant for Learning & Change 2014 (16157823) and from investigator-initiated research grants to the European Atherosclerosis Society-Imperial College London from Amgen, Merck Sharp & Dohme, Sanofi-Aventis, Daiichi Sankyo, and Regeneron. KKR acknowledges support from the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre, UK. KID acknowledges support from a PhD Studentship from NIHR under the Applied Health Research programme for Northwest London, UK (the views expressed in this publication are those of the authors and not necessarily those of the National Health Service, the NIHR, or the Department of Health). TF was supported by a grant from the Czech Ministry of Health (NU20-02-00261). JG receives support from the Canadian Institutes of Health Research. The Austrian Familial Hypercholesterolaemia registry has been supported by funds from the Austrian Heart Foundation and the Tyrolean Regional Government. The Gulf Familial Hypercholesterolaemia registry was done under the auspices of the Gulf Heart Association.
- Published
- 2021
160. The Role of Nutraceuticals in Statin Intolerant Patients
- Author
-
Dimitri P. Mikhailidis, Michel Langlois, Maria-Corina Serban, Rosaria Vincenza Giglio, György Paragh, G.B. John Mancini, Eric Bruckert, Zlatko Fras, Bernhard Paulweber, Daniel Pella, Michal Vrablík, Paul Muntner, Olivier S. Descamps, Gani Bajraktari, Arrigo F G Cicero, Marat V. Ezhov, Željko Reiner, Giuseppe M.C. Rosano, Olena Mitchenko, Angelo Maria Patti, Christos Pitsavos, Patrick M. Moriarty, Dragana Nikolic, Manfredi Rizzo, Nathan D. Wong, Jacek Rysz, Gerald F. Watts, Niki Katsiki, Robert S. Rosenson, Demosthenes B. Panagiotakos, Maciej Banach, Stephan von Haehling, Dragan M. Djuric, Atanas G. Atanasov, Amirhossein Sahebkar, Gustavs Latkovskis, Dragos Vinereanu, UCL - (SLuc) Service de pathologie cardiovasculaire, Banach M., Patti A.M., Giglio R.V., Cicero A.F.G., Atanasov A.G., Bajraktari G., Bruckert E., Descamps O., Djuric D.M., Ezhov M., Fras Z., von Haehling S., Katsiki N., Langlois M., Latkovskis G., Mancini G.B.J., Mikhailidis D.P., Mitchenko O., Moriarty P.M., Muntner P., Nikolic D., Panagiotakos D.B., Paragh G., Paulweber B., Pella D., Pitsavos C., Reiner Z., Rosano G.M.C., Rosenson R.S., Rysz J., Sahebkar A., Serban M.-C., Vinereanu D., Vrablik M., Watts G.F., Wong N.D., Rizzo Manfredi, and Banach M, Patti AM, Giglio RV, Cicero AFG, Atanasov AG, Bajraktari G, Bruckert E, Descamps O, Djuric DM, Ezhov M, Fras Z, von Haehling S, Katsiki N, Langlois M, Latkovskis G, Mancini GBJ, Mikhailidis DP, Mitchenko O, Moriarty PM, Muntner P, Nikolic D, Panagiotakos DB, Paragh G, Paulweber B, Pella D, Pitsavos C, Reiner Ž, Rosano GMC, Rosenson RS, Rysz J, Sahebkar A, Serban MC, Vinereanu D, Vrablík M, Watts GF, Wong ND, Rizzo M
- Subjects
Statin ,medicine.drug_class ,Disease ,cardiovascular risk ,dyslipidemia ,nutraceuticals ,position paper ,statin intolerance ,030204 cardiovascular system & hematology ,Bioinformatics ,Klinikai orvostudományok ,03 medical and health sciences ,0302 clinical medicine ,Nutraceutical ,Ezetimibe ,Statin intolerance ,Red yeast rice ,Medicine ,Humans ,Position paper ,030212 general & internal medicine ,Endothelial dysfunction ,Dyslipidemias ,business.industry ,Clinical Studies as Topic ,Orvostudományok ,medicine.disease ,Cardiovascular risk ,3. Good health ,Dyslipidemia ,Dietary Supplements ,Arterial stiffness ,lipids (amino acids, peptides, and proteins) ,nutraceutical ,Hydroxymethylglutaryl-CoA Reductase Inhibitor ,Nutraceuticals ,Hydroxymethylglutaryl-CoA Reductase Inhibitors ,Cardiology and Cardiovascular Medicine ,business ,medicine.drug ,Human - Abstract
Statins are the most common drugs administered for patients with cardiovascular disease. However, due to statin-associated muscle symptoms, adherence to statin therapy is challenging in clinical practice. Certain nutraceuticals, such as red yeast rice, bergamot, berberine, artichoke, soluble fiber, and plant sterols and stanols alone or in combination with each other, as well as with ezetimibe, might be considered as an alternative or add-on therapy to statins, although there is still insufficient evidence available with respect to long-term safety and effectiveness on cardiovascular disease prevention and treatment. These nutraceuticals could exert significant lipid-lowering activity and might present multiple non–lipid-lowering actions, including improvement of endothelial dysfunction and arterial stiffness, as well as anti-inflammatory and antioxidative properties. The aim of this expert opinion paper is to provide the first attempt at recommendation on the management of statin intolerance through the use of nutraceuticals with particular attention on those with effective low-density lipoprotein cholesterol reduction.
- Published
- 2018
161. Lipid lowering nutraceuticals in clinical practice: position paper from an International Lipid Expert Panel
- Author
-
Demosthenes B. Panagiotakos, Daniel Pella, Michal Vrablík, Dimitri P. Mikhailidis, Alessandro Colletti, Maria-Corina Serban, Zlatko Fras, Laurence S. Sperling, Peter P. Toth, Maciej Banach, György Paragh, Dragos Vinereanu, Nathan D. Wong, Christos Pitsavos, Niki Katsiki, Arrigo F G Cicero, Dragan M. Djuric, Bernhard Paulweber, Željko Reiner, Amirhossein Sahebkar, Gustavs Latkovskis, Marat V. Ezhov, Kausik K. Ray, Michel Langlois, Manfredi Rizzo, Olena Mitchenko, Gani Bajraktari, Olivier Descamps, Cicero, Afg, Colletti, A, Bajraktari, G, Descamps, O, Djuric, Dm, Ezhov, M, Fras, Z, Katsiki, N, Langlois, M, Latkovskis, G, Panagiotakos, Db, Paragh, G, Mikhailidis, Dp, Mitchenko, O, Paulweber, B, Pella, D, Pitsavos, C, Reiner, Ž, Ray, Kk, Rizzo, M, Sahebkar, A, Serban, Mc, Sperling, L, Toth, Pp, Vinereanu, D, Vrablík, M, Wong, Nd, and Banach, M.
- Subjects
0301 basic medicine ,RED YEAST RICE ,Disease ,Pharmacology ,PLACEBO-CONTROLLED TRIAL ,chemistry.chemical_compound ,0302 clinical medicine ,CARDIOVASCULAR RISK-FACTORS ,Family history ,health care economics and organizations ,education.field_of_study ,CONJUGATED LINOLEIC-ACID ,Orvostudományok ,General Medicine ,humanities ,C-REACTIVE PROTEIN ,3. Good health ,DENSITY-LIPOPROTEIN CHOLESTEROL ,030220 oncology & carcinogenesis ,lipids (amino acids, peptides, and proteins) ,nutraceutical ,Life Sciences & Biomedicine ,position paper ,MODERATELY HYPERCHOLESTEROLEMIC SUBJECTS ,medicine.medical_specialty ,RANDOMIZED CONTROLLED-TRIALS ,education ,Population ,Guidelines/Recommendations ,Klinikai orvostudományok ,03 medical and health sciences ,Medicine, General & Internal ,lipid ,General & Internal Medicine ,Internal medicine ,Diabetes mellitus ,medicine ,CORONARY-HEART-DISEASE ,Risk factor ,FATTY LIVER-DISEASE ,Science & Technology ,Cholesterol ,business.industry ,dyslipidemia ,1103 Clinical Sciences ,medicine.disease ,030104 developmental biology ,chemistry ,recommendations ,Etiology ,business ,Dyslipidemia - Abstract
1.1. Cardiovascular disease and dyslipidemia: prevalence and global economic impact Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, reaching 31% of deaths in 2012 [1]. In particular, atherosclerosis and ischemic heart disease (IHD) are the main causes of premature death in Europe and are responsible for 42% of deaths in women and 38% in men under 75 years old [2]. The global economic impact of CVD is estimated to have been US $906 billion in 2015 and is expected to rise by 22% by 2030 [3]. Cardiovascular diseases also represent the major cause of disability in developed countries. It has been estimated that their growing burden could lead to a global increase in loss of disability-adjusted life years (DALYs), from a loss of 85 million DALYs in 1990 to a loss of ~150 million DALYs in 2020, becoming a major non-psychological cause of lost productivity [4]. Several risk factors contribute to the etiology and development of CVD; they are divided into those modifiable through lifestyle changes or by taking a pharmacologic treatment (e.g. for hypertension, smoking, diabetes mellitus, hypercholesterolemia) and those that are not modifiable (age, male gender, and family history) [5]. Elevated total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) blood concentrations are the major modifiable risk factors for coronary heart disease (CHD), whereas high concentrations of plasma high-density lipoprotein cholesterol (HDL-C) in certain conditions are considered protective [6]. Moreover, LDL-C remains a fundamental CV risk factor (and a main target of therapy) even when statins are largely used in the general population [7]. An examination of the data of 18 053 participants aged ≥ 20 years who participated in the National Health and Nutrition Examination Surveys (NHANES) from 1999 to 2006 showed that the unadjusted prevalence of hypercholesterolemia ranged from 53.2% to 56.1% in United States adults [8]. Differences related to gender and race or ethnicity were observed; in particular, a lower rate of control was found among women than men and lower rates of having a cholesterol check and being told about hypercholesterolemia were reported by African Americans and Mexican Americans than whites [8]. A recent report from the American Heart Association confirmed that in the US only 75.7% of children and 46.6% of adults present targeted TC levels (TC < 170 mg/dl for children and < 200 mg/dl for adults, in untreated individuals) [9]. The pattern is similar in other Western countries [10, 11].
- Published
- 2017
162. Lipid-lowering nutraceuticals in clinical practice: position paper from an International Lipid Expert Panel
- Author
-
Maria-Corina Serban, Manfredi Rizzo, Daniel Pella, Michal Vrablík, Nathan D. Wong, Alessandro Colletti, Olivier Descamps, Michel Langlois, Peter P. Toth, Christos Pitsavos, Niki Katsiki, Gani Bajraktari, Olena Mitchenko, Marat V. Ezhov, Arrigo F G Cicero, Kausik K. Ray, György Paragh, Dimitri P. Mikhailidis, Željko Reiner, Bernhard Paulweber, Dragan M. Djuric, Dragos Vinereanu, Amirhossein Sahebkar, Gustavs Latkovskis, Zlatko Fras, Laurence S. Sperling, Maciej Banach, Demosthenes B. Panagiotakos, Cicero, Afg, Colletti, A, Bajraktari, G, Descamps, O, Djuric, Dm, Ezhov, M, Fras, Z, Katsiki, N, Langlois, M, Latkovskis, G, Panagiotakos, Db, Paragh, G, Mikhailidis, Dp, Mitchenko, O, Paulweber, B, Pella, D, Pitsavos, C, Reiner, Ž, Ray, Kk, Rizzo, M, Sahebkar, A, Serban, Mc, Sperling, L, Toth, Pp, Vinereanu, D, Vrablík, M, Wong, Nd, and Banach, M.
- Subjects
Phytochemicals ,Medicine (miscellaneous) ,030204 cardiovascular system & hematology ,Pharmacology ,Intestinal absorption ,0302 clinical medicine ,Risk Factors ,Drug Interactions ,030212 general & internal medicine ,Randomized Controlled Trials as Topic ,Nutrition and Dietetics ,Evidence-Based Medicine ,Orvostudományok ,3. Good health ,Observational Studies as Topic ,Liver ,Cardiovascular Diseases ,Fatty Acids, Unsaturated ,lipids (amino acids, peptides, and proteins) ,nutraceutical ,position paper ,medicine.medical_specialty ,Statin ,Combination therapy ,medicine.drug_class ,Klinikai orvostudományok ,03 medical and health sciences ,Meta-Analysis as Topic ,lipid ,medicine ,Humans ,Intensive care medicine ,Life Style ,Triglycerides ,Dyslipidemias ,business.industry ,Probiotics ,dyslipidemia ,Cholesterol, HDL ,Evidence-based medicine ,Cholesterol, LDL ,medicine.disease ,Residual risk ,Intestinal Absorption ,recommendations ,Dietary Supplements ,Position paper ,Hydroxymethylglutaryl-CoA Reductase Inhibitors ,business ,Dyslipidemia - Abstract
In recent years, there has been growing interest in the possible use of nutraceuticals to improve and optimize dyslipidemia control and therapy. Based on the data from available studies, nutraceuticals might help patients obtain theraputic lipid goals and reduce cardiovascular residual risk. Some nutraceuticals have essential lipid-lowering properties confirmed in studies; some might also have possible positive effects on nonlipid cardiovascular risk factors and have been shown to improve early markers of vascular health such as endothelial function and pulse wave velocity. However, the clinical evidence supporting the use of a single lipid-lowering nutraceutical or a combination of them is largely variable and, for many of the nutraceuticals, the evidence is very limited and, therefore, often debatable. The purpose of this position paper is to provide consensus-based recommendations for the optimal use of lipid-lowering nutraceuticals to manage dyslipidemia in patients who are still not on statin therapy, patients who are on statin or combination therapy but have not achieved lipid goals, and patients with statin intolerance. This statement is intended for physicians and other healthcare professionals engaged in the diagnosis and management of patients with lipid disorders, especially in the primary care setting.
- Published
- 2017
163. Evolocumab and clinical outcomes in patients with cardiovascular disease
- Author
-
Sabatine, Marc S., Giugliano, Robert P., Keech, Anthony C., Honarpour, Narimon, Wiviott, Stephen D., Murphy, Sabina A., Kuder, Julia F., Wang, Huei, Liu, Thomas, Wasserman, Scott M., Sever, Peter S., Pedersen, Fish MP, Terje R., Abrahamsen, Te, Im, K, Kanevsky, E, Bonaca, Mp, Lira Pineda, A, Hanlon, K, Knusel, B, Somaratne, R, Kurtz, C, Scott, R, Accini Mendoza JL, Amerena, J, Badariene, J, Burgess, L, Ceska, R, Charng, Mj, Choi, D, Cobos, Jl, Dan, Ga, De Ferrari GM, Deedwania, Pc, Chopra, Vk, Erglis, A, Ezhov, Mv, Ferreira, J, Filipová, S, Gaciong, Za, Pasierski, T, Georgiev, Bg, Gonzalez-Galvez, G, Gouni-Berthold, I, Schäufele, T, Hirayama, A, Huber, K, Rammer, M, Kjaerulf Jensen, H, Wermuth, S, Jiang, L, Jukema, Jw, Kraydashenko, O, Leiter, La, Lewis, Bs, López-Miranda, J, Lorenzatti, Aj, Mach, F, Mcadam, B, Nilsson, L, Olsson, Å, Rallidis, L, Rogelio, Gg, Kerr Saraiva JF, Scheen, A, Schiele, F, Scott, Rs, Connolly, D, Siu, Cw, Tay, L, Thorgeirsson, G, Tikkanen, Mj, Tokgozoglu, Sl, Toth, K, Viigimaa, M, Wan Ahmad WA, Hennekens, Ch, Andreotti, F, Baigent, C, Brown, Wv, Davis, Br, Newcomer, Jw, Wood, Sk, Larosa, J, Ansell, B, Olsson, A, Lowe, C, Zahn, L, Awtry, E, Berger, C, Croce, K, Desai, A, Gelfand, E, Ho, C, Leeman, D, Link, M, Norden, A, Pande, A, Rost, N, Ruberg, F, Silverman, S, Singhal, A, Vita, J, Mackinnon, I, Vogel, Dr, Leon de la Fuente, R, Perna, E, Amuchastegui, M, Pacora, F, Hershson, A, Blumberg, E, Glenny, Ja, Colombo, H, Cuadrado, Ja, Nicolosi, L, Rojas, Cg, Ulla, Mr, Hasbani, Eg, Cuneo, C, Lopez Santi RG, Sanabria, Hd, Hrabar, A, Lozada, A, Begg, A, Lehman, S, Wittert, G, Juergens, C, Kostner, K, Beltrame, J, Simpson, R, Sinhal, A, Adams, M, Kritharides, L, Roberts Thomson, P, Cross, D, Thompson, P, Van Gaal, W, Cox, N, Farshid, A, Hammett, C, Garrahy, P, Prasan, A, Horrigan, M, Ebenbichler, C, Hanusch, U, Prager, R, Schernthaner, G, Luger, A, Siostrzonek, P, Toplak, H, Bergler-Klein, J, Paulweber, B, Sinzinger, H, Buysschaert, I, Thoeng, J, Vandekerckhove, H, Catez, E, Verheye, S, Descamps, O, Hoffer, E, Wollaert, B, Chenu, P, van de Borne, P, De Meulemeester, M, Friart, A, Charlier, F, De Raedt, H, Rietzschel, E, Roelandt, R, Lalmand, J, Tavares Russo LA, Reis, G, Duarte Barbosa EC, Vidotti, Mh, Fernandes Manenti ER, Dutra, O, Leaes, Pe, Rech, Rl, Bertolim Precoma, D, Nicolau, Jc, Amoedo, R, Eliaschewitz, Fg, Pereira, A, Kurtz Lisboa HR, Soares Piegas, L, Cunha Borges JL, Ferreira Rossi PR, Pimentel Filho, P, Bodanese, Lc, de Sa Cunha, R, Moura Jorge JC, Ardito, Wr, Barroso de Souza WK, Hissa, M, Izar, Mc, Manolova, A, Kitova, L, Kinova, E, Tzekova, M, Velchev, V, Tarnovska-Kadreva, R, Gotchev, D, Petrov, I, Raev, D, Trendafilova-Lazarova, D, Yotov, Y, Lazov, P, Rahimi, S, St Amour, E, Constance, C, Pesant, Y, Hess, A, Anderson, T, Sussex, B, Henein, S, Tsoukas, G, Pandey, As, Bergeron, J, Hart, R, Gosselin, G, Chehayeb, R, Hamet, P, Hartleib, M, Mukherjee, A, Halperin, F, Petrella, R, Bhargava, R, Lonn, E, Sabbah, E, Bata, I, Cha, J, Gaudet, D, Chapman, K, Murthy, D, Nigro, F, Rupka, D, Gossard, D, Gupta, M, Dowell, A, Mansour, S, Baass, A, Geadah, C, Huynh, T, Peterson, S, Poirier, P, Sabe-Affaki, G, Vertes, G, Crowley, D, Duchesne, L, Pincetti Jofre CP, Potthoff Cardenas, S, Conejeros Kindel, C, Saavedra Gajardo VA, Lanas Zanetti, F, Sepulveda Varela PA, Stockins Fernandez BA, Li, W, Li, D, Zhao, S, Li, Z, Wang, J, Yang, Y, Zhang, L, Yang, P, Zhang, X, Huang, H, Xue, L, Zheng, Z, Huang, W, Dai, H, Su, H, Zeng, X, Zheng, Y, Tang, Y, Yao, Z, Sun, Y, Du, Y, Ge, Z, Yan, J, Chen, X, Liu, F, Pei, H, Yang, X, Cui, H, Gu, Y, Yang, Z, Li, J, Lian, Y, Cui, Y, Wang, D, Jiang, J, Li, X, Chen, J, Mo, Z, Xu, P, He, Y, Zhou, C, Qu, P, Zhu, Y, Liu, Y, Shen, X, Gao, X, Terront Lozano MA, Moncada Corredor MA, Hernandez Triana, E, Botero Lopez, R, Coronel Arroyo JA, Quintero Baiz AE, Sanchez Vallejo, G, Arana Londoño, C, Molina de Salazar DI, Castellanos Bueno, R, Manzur Jattin, F, Cure Cure CA, Sotomayor Herazo, A, Spinar, J, Hala, T, Machkova, M, Klimsa, Z, Polasek, R, Jerabek, O, Kazdera, P, Pozdisek, Z, Vaclavik, J, Frana, P, Elbl, L, Kucera, D, Kryza, R, Malecha, J, Reichert, P, Sochor, K, Ludka, O, Kellnerova, I, Peterka, K, Zidkova, E, Cech, V, Brabec, T, Fiserova, N, Kvasnicka, J, Rosolova, H, Nemecek, E, Adamkova, V, Dunaj, M, Pojsl, S, Cepelak, M, Podpera, I, Kuchar, L, Rysava, D, Burianova, H, Spinarova, L, Skrobakova, J, Charvat, J, Homza, M, Zemanek, J, Koleckar, P, Karen, I, Krupicka, J, Blaha, V, Matuska, J, Brotanek, J, Cifkova, R, Kuchar, R, Vomacka, Z, Kosek, Z, Hulinsky, V, Krejcova, H, Kuchar, J, Jelinek, Z, Jelinek, P, Markdanner Lindgren, L, Saetre Lihn, A, Korsgaard Thomsen, K, Bronnum-Schou, J, Nielsen, H, Nielsen, T, Egstrup, K, Klausen, Ic, Mickley, H, Hove, J, Jeppesen, J, Melchior, T, Schmidt, Eb, Valter, I, Rosenthal, A, Kaik, J, Kork, A, Alt, I, Strand, J, Nieminen, S, Kahri, J, Suomi, J, Nyman, K, Strandberg, Te, Piippo, T, Savolainen, M, Vikman, S, Pucheu, Y, Cariou, B, Henry, P, Ferrari, E, Montalescot, G, Ferrieres, J, Roubille, F, Bonnet, B, Angoulvant, D, Range, G, Bammert, A, Delarche, N, Mariat, C, Cayla, G, Durlach, V, Coisne, D, Paillard, F, Rouzier, R, Goralski, M, Khanoyan, P, Cottin, Y, Ziegler, O, Khalife, K, Le Corvoisier, P, Motreff, P, Spaulding, C, Vanbelle, E, Bourhaial, H, Opitz, C, Kahrmann, G, Contzen, C, Appel, K, Schenkenberger, I, Rinke, A, Trenk, D, Maus, O, Karakas, M, Hanefeld, M, Darius, H, Hetzel, G, Münzel, T, Wöhrle, J, Stawowy, P, Marten, I, Isermann, B, Kast, P, Vorpahl, M, Bosiljanoff, P, Hengstenberg, C, Kassner, U, Salbach, P, Fischer, M, Steiner, S, Wagner, S, Kraatz, U, von Hodenberg, E, Weyland, K, Mantas, I, Tziakas, D, Bousboulas, S, Patsilinakos, S, Mertzanos, G, Panagoulis, C, Bilianou, H, Skoumas, I, Elisaf, M, Manolis, A, Moschos, N, Kochiadakis, G, Ntaios, G, Richter, D, Athyros, V, Kolovou, G, Danias, P, Melidonis, A, Fan, Kyy, Siu, Sc, Hornyik, A, Lakatos, F, Zilahi, Z, Nagy, K, Laszlo, Z, Peterfai, E, Lupkovics, G, Andreka, P, Merkely, B, Herczeg, B, Piros, Ga, Salamon, C, Mark, L, Papp, A, Szakal, I, Edes, I, Mohacsi, A, Tomcsanyi, J, Hajko, E, Nagy, A, Papp, E, Kiss, R, Karadi, I, Sigurdsson, A, Jain, A, Pai, R, Kothiwale, V, Kulkarni, G, Mahajan, A, Aggarwal, S, Mehta, V, Rajadhyaksha, G, Joshi, A, Khandait, V, Parmar, M, Tyagi, S, Airody Govinda, R, Dwivedi, Sk, Parikh, K, Pothineni, Rb, Solanki, B, O’Donnell, M, Crean, P, Barton, J, Shechter, M, Shotan, A, Klutstein, M, Chorin, E, Gavish, D, Kracoff, O, Atar, S, Rigler, S, Hasin, Y, Schiff, E, Merlini, P, Rapezzi, C, Pirro, M, Gonnelli, S, Floresta, Am, Mennuni, M, Ardissino, D, Senni, M, Marenzi, G, Marcucci, R, Sampietro, T, Cosmi, F, Perrone Filardi, P, De Caterina, R, Fedele, Francesco, Moretti, L, Biasucci, Lm, Ferri, C, Go, Y, Kiyosue, A, Higashi, Y, Tokunaga, T, Kawasaki, T, Sakagami, S, Namba, S, Saku, K, Oku, K, Arakawa, T, Iida, H, Nakamura, Y, Yamamoto, K, Hata, Y, Katsuda, Y, Koga, Y, Shimizu, M, Uehara, H, Kajiyama, S, Okamoto, H, Shinozaki, T, Fujino, Y, Funazaki, T, Higa, N, Kaigawa, K, Koike, A, Nakane, H, Sato, K, Satoh, Y, Shirasawa, K, Sugino, H, Tanabe, J, Uemura, O, Yoshimichi, G, Akai, A, Himeno, H, Inage, T, Inoko, M, Kadokami, T, Noguchi, Y, Yamashita, K, Yasumura, Y, Yuge, M, Hosokawa, S, Kawamitsu, K, Kozuma, K, Matsuo, H, Nakashima, E, Okada, M, Wada, A, Yokoya, K, Iwade, K, Kawabata, K, Tanno, H, Ako, J, Fujita, H, Izumiya, Y, Kanno, M, Nunohiro, T, Ohmura, H, Ueno, T, Kakurina, N, Jasinkevica, I, Stukena, I, Veze, I, Eglite, R, Teterovska, D, Sime, I, Strazdiene, V, Venceviciene, L, Gustiene, O, Radzeviciene-Jurgute, R, Kucinskiene, A, Maskon, O, Lee, Cy, Erng, T, Gan, Hw, Mohamed Yusof AK, Ramanathan, Gl, Liew, H, Lopez Alvarado, A, Nevarez Ruiz LA, De los Rios Ibarra MO, Bazzoni Ruiz AE, Ramos Lopez GA, Llamas Esperon GA, De la Peña Topete GDJ, Violante Ortiz RM, Illescas Diaz JJ, Leon Gonzalez, S, Sanchez Diaz CJ, Mendez Machado GF, Venegas Carrillo LA, Aldrete Velasco JA, Cardona Muñoz EG, Leiva Pons JL, Perez Alva JC, van der Zwaan, C, Oomen, A, van de Wal, R, Magro, M, Boswijk, D, Janus, C, Groutars, R, Tonino, W, Cornel, Jh, Oude Ophuis, A, Troquay, R, Liem, A, Westendorp, I, Van Hessen, M, Lok, D, De Nooijer, C, Den Hartog, F, Van Beek, E, Bendermacher, P, Jansen, R, Römer, T, Rensing, B, Hersbach, F, Herrman, J, Ladyjanskaia, G, Karalis, I, Linssen, G, Bokern, M, Visman, A, Kooij, A, Monajemi, H, Lieverse, A, Baker, J, Tie, S, Risberg, K, Hysing, J, Pedersen, T, Hoivik, Ho, Norheim, P, Solnor, L, Hovland, A, Kjaernli, T, Jocson, G, Coching, Rm, Batalla, E, Go, A, Habaluyas, R, Barcinas, R, Sy, Ra, Estepar, Ra, Germar, A, Trebacz, J, Szymkowiak, K, Wnetrzak-Michalska, R, Kopaczewski, J, Przekwas-Jaruchowska, M, Kania, G, Zabowka, M, Mirek-Bryniarska, E, Dabrowska, M, Napora, P, Konieczny, M, Spyra, J, Lysek, R, Pijanowski, Z, Grzegorzewski, B, Bednarkiewicz, Z, Kinasz, L, Antkowiak-Piatyszek, K, Stania, K, Szpajer, M, Staneta, P, Skonieczny, G, Ksiezycka-Majczynska, E, Blicharski, T, Piepiorka, M, Wozakowska-Kaplon, B, Zechowicz, T, Ilkowski, J, Lubiszewska, B, Hiczkiewicz, J, Wierzbicka, K, Kosior, D, Garbocz, P, Kubica, J, Raczak, G, Wozniak, I, Cygler, J, Kramarczuk, E, Bystryk, L, Pentela-Nowicka, J, Dabrowski, M, Podolec, P, Zieba, B, Mosiewicz, J, Dubaniewicz, W, Banach, M, Tyszecka, G, Lepich, T, Rychlewska-Hanczewska, A, Guzik, T, Monteiro, P, Pereira, H, Oliveira, L, Matos, P, Soares Goncalves, S, Leitao, A, Vasco Salgado, A, Timoteo, At, Pintilei, E, Badila, E, Militaru, C, Tudoran, M, Arsenescu-Georgescu, C, Mitu, F, Zdrenghea, D, Lighezan, D, Teodorescu, I, Popescu, Mi, Coman, I, Vintila, Mm, Vishnevsky, A, Lukyanov, Y, Blokhin, A, Kostenko, V, Shvarts, Y, Markov, V, Motylev, I, Dronov, D, Sherenkov, A, Barbarash, O, Shutemova, E, Bolshakova, O, Kobalava, Z, Voevoda, M, Treshkur, T, Zrazhevskiy, K, Pimenov, L, Solovev, O, Tarasov, N, Arkhipov, M, Freidlin, M, Shalaev, S, Yakhontova, P, Shustov, S, Goloshchekin, B, Panov, A, Bart, B, Bubnova, M, Gordeev, I, Osipova, I, Tereshenko, S, Solovieva, E, Meshkov, A, Zateyshchikov, D, Tan, Jl, Subramaniam, T, Pella, D, Fulop, P, Antalik, L, Dzupina, A, Banikova, A, Sosovec, D, Urgeova, L, Mazur, J, Hranai, M, Banik, M, Vinanska, D, Lennerova, J, Kovar, F, Pastrnakova, E, Uhliar, R, Blasko, P, Gonsorcik, J, Lukacova, J, Oriesek, R, Hatalova, K, du Toit, M, Ebrahim, I, Vawda, G, Lipschitz, S, Blignaut, S, Engelbrecht, J, Coetzer, Tf, Pretorius, M, Urbach, D, Badat, A, Pillay, S, Van Zyl, L, Abelson, M, van der Walt, E, Moodley, R, Jacovides, A, Oosthuysen, Wm, Klug, E, Lottering, H, Kok, J, Saaiman, J, Dawood, S, De Jong DM, Kapp, C, Makotoko, E, Bayat, J, Sarvan, M, Vally, T, Stapelberg, A, Kim, M, Bae, J, Cho, Y, Kim, S, Han, Kh, Her, S, Kim, B, Lee, S, Hong, B, Kim, W, Rha, S, Jeong, M, Shin, Gj, Vida Gutierrez, M, Valdes Chavarri, M, Pinto Sala, X, Gonzalez Juanatey JR, Civeira Murillo, F, Zamorano Gomez JL, Lekuona Goya, I, Iñiguez Romo, A, Cordero Fort, A, Ascaso Gimilio JF, Millan Nuñez-Cortes, J, Lindholm, C, Söderberg, S, Suutari, A, Berglund, S, Mooe, T, Kusiak, D, Bandh, S, Dahlén, G, Olsson, S, Witt, N, Tydén, P, Johansson, P, Cizinsky, S, Falck, G, Pettersson, Si, Rasmanis, G, Östergren, J, Moccetti, T, Beer, Hj, Eberli, F, Krähenbühl, S, Linka, A, Ackermann, D, Michel, P, Yeh, H, Tsai, Cf, Wu, C, Hsia, C, Juang, J, Hsieh, I, Lai, W, Huang, C, Hsieh, Y, Sahin, T, Duzenli, M, Yigit, Z, Demir, M, Yilmaz, Mb, Muderrisoglu, Ih, Kirma, C, Ercan, E, Kayikcioglu, L, Balbay, Y, Lymar, I, Kulynych, O, Prokhorov, O, Karpenko, O, Kraіz, I, Vakaliuk, I, Stanislavchuk, M, Korzh, O, Rudyk, I, Zhurba, S, Svishchenko, Y, Tseluyko, V, Gyrina, O, Reshotko, D, Kopytsya, M, Volkov, V, Myshanych, G, Rebrov, B, Rishko, M, Rudenko, L, Shatylo, V, Parkhomenko, O, Yena, L, Golovchenko, O, Sorokina, I, Malynovsky, Y, Ivan, P, Blagden, M, Dear, H, Mathew, A, Lagocki, S, Kondagunta, V, Ahsan, A, Mckinnon, C, Douglas, F, Thom, S, Fiore, G, Caulfield, M, Lynch, M, Thomas, H, Bain, S, Hall, A, Mcnally, D, Fisher, M, Keeling, P, Al-Bahrani, A, Lip, G, Ellery, A, Purohit, J, Travill, C, Cappuccio, F, Davis, G, Gaunt, R, Adlam, D, Asamoah, N, Jaafar, F, Mccormack, T, Jupp, B, Pye, M, Ainsworth, P, Chauhan, A, Paul, N, Fairlie, H, Fox, C, Muzulu, S, Trevelyan, J, Aggarwal, R, Issa, B, Saravanan, P, Cruickshank, K, Gorog, D, Heller, S, Newby, D, Nicolson, A, Hare, Po, Donnelly, P, Rutherfurd, S, de Belder, M, Finlayson, J, Harvey, J, Hoye, A, Kingston, D, Sarkar, D, Negahban, A, Webster, J, Wyatt, N, Muir, S, Cummings, M, Mackenzie, I, Senior, R, Capps, N, Fotherby, K, Mcintyre, H, Aldegather, J, Dixon, L, Saksena, R, Butler, R, Ramstad, D, Pierpont, B, Levinson, D, Mohammed, A, Haddad, T, Goel, A, Dave, K, Haught, Wh, Desire, A, Hershon, K, Napoli, M, Tami, L, Rothschild, R, Khurana, S, Gupta, D, Cheung, D, Hearne, S, Grubb, S, Miller, A, Baird, I, Marcus, A, Srivastava, S, Forgosh, L, Fritz, R, Mays, M, Bertolet, B, Reddy, J, Khan, M, Nakhle, S, Dill, S, Fishbein, G, Khan, B, Marais, H, Reschak, M, Malone, M, Nadar, V, Whitney, R, Reichman, A, Reyes, H, El Shahawy, M, Rabinowitz, A, Weinstein, D, Farhat, N, Onyema, D, Potu, R, Runquist, L, Barnum, O, Crater, T, Fialkow, J, Shah, A, Thompson, C, Wiseman, A, Doyle, T, Henderson, D, Herzog, W, Schnitzler, R, Carr, K, Davis, M, Nagajothi, N, Olsen, S, Rogers, W, Rubino, J, Singh, I, Tarleton, G, Bhagwat, R, Clardy, D, Jardula, M, Robinson, J, Torres, M, Vijay, N, Farris, N, Lillo, J, Moriarty, P, Recknor, C, Berlacher, P, Christensen, T, Gabra, N, Issa, M, Janik, M, Lawless, A, Molter, D, Stout, E, Brezina, B, Claxton, E, Linsky, R, Poock, J, Remler, R, Roseman, H, Schramm, E, Al-Joundi, T, Amin, J, Hitchcock, J, Isserman, S, Kirstein, J, Rider, J, Shalek, M, Sherman, H, Bernstein, M, Chandra, L, Hatharasinghe, R, Ibrahim, H, Iteld, B, Linzmeyer, K, Seaton, B, Zeig, S, Christofides, E, Dunbar, R, Griffin, S, Kohli, N, Koren, M, Pharr, W, Purdy, D, Spencer, R, Yeoman, G, Banerjee, S, Cheek, Hb, Engel, E, Hamroff, G, Huling, R, Kozlowski, L, Levin, P, Makam, S, Meengs, M, Bhushan, R, Erickson, B, Herman, L, Lo, E, Mcdowell, E, Mcgrew, F, Miller, M, Ord, J, Webel, R, Wilhoit, G, Wise, J, Yang, E, Budoff, M, Collins, J, Dauber, I, Dobkin, L, Focil, A, Gandy, W, Pasquini, J, Ramos, M, Rodriguez, D, Rosenson, R, Sanford, K, Schlau, A, Snyder, B, Stonesifer, L, Tang, A, De Souza, J, Elam, M III, French, J, Guyton, J, Hage Korban, E, Kereiakes, D, King, M, Loh, I, Navarro, J, Simons, R, Tobin, T, Younis, L, Aboufakher, R, Baldari, D, Ballantyne, C, Broughton, R, Eaton, C, Johnston, J, Simon, W, Thomson, S, Vora, K, Youngman, D, Alzohaili, O, Auerbach, E, Brown, C, Burrough, B, Chen, Y, Gilpatrick, M, Landzberg, J, Mitchell, C, Rice, L, Rubenfire, M, Sofley, Cw, Strobl, D, Atassi, K, Davila, W, Diogo, J, Fagan, T, Joffe, I, Krishna, J, Osea, E, Penny, W, Rowe, W, Shapiro, M, Welker, J, Benton, R, Dobratz, D, Fortuin, F, Graham, J, Henry, B, Kusnick, B, Lutskiy, M, Mcrae, A, Saway, W, Scott, J, Shah, M, Weinberg, B, Zarich, S, Acheatel, R, Case, C, Earl, J, Fernandez, S, Giugliano, G, Handelsman, Y, Hermany, P, Holder, S, Kashyap, M, Khan, A, Lader, E, Peniston, J, Raoof, T, Sacco, J, Shore, K, Spriggs, D, Stringam, S, Tahirkheli, N, Delgado, E, Derian, W, Greenwald, J, Harris, M, Jackson, R, Marhefka, G, Mcelveen, W, Mooss, A, Morris, P, Murray, J, Pearlstein, P, Raisinghani, A, Rezkalla, S, Sakhrani, L, Schreibman, D, Shaoulian, E, Steinsapir, J, Yataco, A, De La Cruz, A, Fredrick, M, Goldenberg, E, Lee, D, Mccullum, K, Mclellan, B, Stephens, L, Wilson, S, Alfieri, A, Mandviwala, M, Orourke, D, Samal, A, Schmedtje, J, Waxman, F, Carhart, R, Clements, B, Dyke, C, Ghali, J, Gruberg, L, Hack, T, Jehle, A, Pogue, B, Schooley, C, Shifrin, G., National Institute for Health Research, Amgen Inc, University of Zurich, Sabatine, Marc S, Sabatine, M, Giugliano, R, Keech, A, Honarpour, N, Wiviott, S, Murphy, S, Kuder, J, Wang, H, Liu, T, Wasserman, S, Sever, P, Pedersen, T, Fish, M, Abrahamsen, T, Im, K, Kanevsky, E, Bonaca, M, Lira Pineda, A, Hanlon, K, Knusel, B, Somaratne, R, Kurtz, C, Scott, R, Accini Mendoza, J, Amerena, J, Badariene, J, Burgess, L, Ceska, R, Charng, M, Choi, D, Cobos, J, Dan, G, De Ferrari, G, Deedwania, P, Chopra, V, Erglis, A, Ezhov, M, Ferreira, J, Filipova, S, Gaciong, Z, Pasierski, T, Georgiev, B, Gonzalez-Galvez, G, Gouni-Berthold, I, Schaufele, T, Hirayama, A, Huber, K, Rammer, M, Kjaerulf Jensen, H, Wermuth, S, Jiang, L, Jukema, J, Kraydashenko, O, Leiter, L, Lewis, B, Lopez-Miranda, J, Lorenzatti, A, Mach, F, Mcadam, B, Nilsson, L, Olsson, A, Rallidis, L, Rogelio, G, Kerr Saraiva, J, Scheen, A, Schiele, F, Connolly, D, Siu, C, Tay, L, Thorgeirsson, G, Tikkanen, M, Tokgozoglu, S, Toth, K, Viigimaa, M, Wan Ahmad, W, Hennekens, C, Andreotti, F, Baigent, C, Brown, W, Davis, B, Newcomer, J, Wood, S, Larosa, J, Ansell, B, Lowe, C, Zahn, L, Awtry, E, Berger, C, Croce, K, Desai, A, Gelfand, E, Ho, C, Leeman, D, Link, M, Norden, A, Pande, A, Rost, N, Ruberg, F, Silverman, S, Singhal, A, Vita, J, Mackinnon, I, Vogel, D, Leon de la Fuente, R, Perna, E, Amuchastegui, M, Pacora, F, Hershson, A, Blumberg, E, Glenny, J, Colombo, H, Cuadrado, J, Nicolosi, L, Rojas, C, Ulla, M, Hasbani, E, Cuneo, C, Lopez Santi, R, Sanabria, H, Hrabar, A, Lozada, A, Begg, A, Lehman, S, Wittert, G, Juergens, C, Kostner, K, Beltrame, J, Simpson, R, Sinhal, A, Adams, M, Kritharides, L, Roberts Thomson, P, Cross, D, Thompson, P, Van Gaal, W, Cox, N, Farshid, A, Hammett, C, Garrahy, P, Prasan, A, Horrigan, M, Ebenbichler, C, Hanusch, U, Prager, R, Schernthaner, G, Luger, A, Siostrzonek, P, Toplak, H, Bergler-Klein, J, Paulweber, B, Sinzinger, H, Buysschaert, I, Thoeng, J, Vandekerckhove, H, Catez, E, Verheye, S, Descamps, O, Hoffer, E, Wollaert, B, Chenu, P, van de Borne, P, De Meulemeester, M, Friart, A, Charlier, F, De Raedt, H, Rietzschel, E, Roelandt, R, Lalmand, J, Tavares Russo, L, Reis, G, Duarte Barbosa, E, Vidotti, M, Fernandes Manenti, E, Dutra, O, Leaes, P, Rech, R, Bertolim Precoma, D, Nicolau, J, Amoedo, R, Eliaschewitz, F, Pereira, A, Kurtz Lisboa, H, Soares Piegas, L, Cunha Borges, J, Ferreira Rossi, P, Pimentel Filho, P, Bodanese, L, de Sa Cunha, R, Moura Jorge, J, Ardito, W, Barroso de Souza, W, Hissa, M, Izar, M, Manolova, A, Kitova, L, Kinova, E, Tzekova, M, Velchev, V, Tarnovska-Kadreva, R, Gotchev, D, Petrov, I, Raev, D, Trendafilova-Lazarova, D, Yotov, Y, Lazov, P, Rahimi, S, St Amour, E, Constance, C, Pesant, Y, Hess, A, Anderson, T, Sussex, B, Henein, S, Tsoukas, G, Pandey, A, Bergeron, J, Hart, R, Gosselin, G, Chehayeb, R, Hamet, P, Hartleib, M, Mukherjee, A, Halperin, F, Petrella, R, Bhargava, R, Lonn, E, Sabbah, E, Bata, I, Cha, J, Gaudet, D, Chapman, K, Murthy, D, Nigro, F, Rupka, D, Gossard, D, Gupta, M, Dowell, A, Mansour, S, Baass, A, Geadah, C, Huynh, T, Peterson, S, Poirier, P, Sabe-Affaki, G, Vertes, G, Crowley, D, Duchesne, L, Pincetti Jofre, C, Potthoff Cardenas, S, Conejeros Kindel, C, Saavedra Gajardo, V, Lanas Zanetti, F, Sepulveda Varela, P, Stockins Fernandez, B, Li, W, Li, D, Zhao, S, Li, Z, Wang, J, Yang, Y, Zhang, L, Yang, P, Zhang, X, Huang, H, Xue, L, Zheng, Z, Huang, W, Dai, H, Su, H, Zeng, X, Zheng, Y, Tang, Y, Yao, Z, Sun, Y, Du, Y, Ge, Z, Yan, J, Chen, X, Liu, F, Pei, H, Yang, X, Cui, H, Gu, Y, Yang, Z, Li, J, Lian, Y, Cui, Y, Wang, D, Jiang, J, Li, X, Chen, J, Mo, Z, Xu, P, He, Y, Zhou, C, Qu, P, Zhu, Y, Liu, Y, Shen, X, Gao, X, Terront Lozano, M, Moncada Corredor, M, Hernandez Triana, E, Botero Lopez, R, Coronel Arroyo, J, Quintero Baiz, A, Sanchez Vallejo, G, Arana Londono, C, Molina de Salazar, D, Castellanos Bueno, R, Manzur Jattin, F, Cure Cure, C, Sotomayor Herazo, A, Spinar, J, Hala, T, Machkova, M, Klimsa, Z, Polasek, R, Jerabek, O, Kazdera, P, Pozdisek, Z, Vaclavik, J, Frana, P, Elbl, L, Kucera, D, Kryza, R, Malecha, J, Reichert, P, Sochor, K, Ludka, O, Kellnerova, I, Peterka, K, Zidkova, E, Cech, V, Brabec, T, Fiserova, N, Kvasnicka, J, Rosolova, H, Nemecek, E, Adamkova, V, Dunaj, M, Pojsl, S, Cepelak, M, Podpera, I, Kuchar, L, Rysava, D, Burianova, H, Spinarova, L, Skrobakova, J, Charvat, J, Homza, M, Zemanek, J, Koleckar, P, Karen, I, Krupicka, J, Blaha, V, Matuska, J, Brotanek, J, Cifkova, R, Kuchar, R, Vomacka, Z, Kosek, Z, Hulinsky, V, Krejcova, H, Kuchar, J, Jelinek, Z, Jelinek, P, Markdanner Lindgren, L, Saetre Lihn, A, Korsgaard Thomsen, K, Bronnum-Schou, J, Nielsen, H, Nielsen, T, Egstrup, K, Klausen, I, Mickley, H, Hove, J, Jeppesen, J, Melchior, T, Schmidt, E, Valter, I, Rosenthal, A, Kaik, J, Kork, A, Alt, I, Strand, J, Nieminen, S, Kahri, J, Suomi, J, Nyman, K, Strandberg, T, Piippo, T, Savolainen, M, Vikman, S, Pucheu, Y, Cariou, B, Henry, P, Ferrari, E, Montalescot, G, Ferrieres, J, Roubille, F, Bonnet, B, Angoulvant, D, Range, G, Bammert, A, Delarche, N, Mariat, C, Cayla, G, Durlach, V, Coisne, D, Paillard, F, Rouzier, R, Goralski, M, Khanoyan, P, Cottin, Y, Ziegler, O, Khalife, K, Le Corvoisier, P, Motreff, P, Spaulding, C, Vanbelle, E, Bourhaial, H, Opitz, C, Kahrmann, G, Contzen, C, Appel, K, Schenkenberger, I, Rinke, A, Trenk, D, Maus, O, Karakas, M, Hanefeld, M, Darius, H, Hetzel, G, Munzel, T, Wohrle, J, Stawowy, P, Marten, I, Isermann, B, Kast, P, Vorpahl, M, Bosiljanoff, P, Hengstenberg, C, Kassner, U, Salbach, P, Fischer, M, Steiner, S, Wagner, S, Kraatz, U, von Hodenberg, E, Weyland, K, Mantas, I, Tziakas, D, Bousboulas, S, Patsilinakos, S, Mertzanos, G, Panagoulis, C, Bilianou, H, Skoumas, I, Elisaf, M, Manolis, A, Moschos, N, Kochiadakis, G, Ntaios, G, Richter, D, Athyros, V, Kolovou, G, Danias, P, Melidonis, A, Fan, K, Siu, S, Hornyik, A, Lakatos, F, Zilahi, Z, Nagy, K, Laszlo, Z, Peterfai, E, Lupkovics, G, Andreka, P, Merkely, B, Herczeg, B, Piros, G, Salamon, C, Mark, L, Papp, A, Szakal, I, Edes, I, Mohacsi, A, Tomcsanyi, J, Hajko, E, Nagy, A, Papp, E, Kiss, R, Karadi, I, Sigurdsson, A, Jain, A, Pai, R, Kothiwale, V, Kulkarni, G, Mahajan, A, Aggarwal, S, Mehta, V, Rajadhyaksha, G, Joshi, A, Khandait, V, Parmar, M, Tyagi, S, Airody Govinda, R, Dwivedi, S, Parikh, K, Pothineni, R, Solanki, B, O'Donnell, M, Crean, P, Barton, J, Shechter, M, Shotan, A, Klutstein, M, Chorin, E, Gavish, D, Kracoff, O, Atar, S, Rigler, S, Hasin, Y, Schiff, E, Merlini, P, Rapezzi, C, Pirro, M, Gonnelli, S, Floresta, A, Mennuni, M, Ardissino, D, Senni, M, Marenzi, G, Marcucci, R, Sampietro, T, Cosmi, F, Perrone Filardi, P, De Caterina, R, Fedele, F, Moretti, L, Biasucci, L, Ferri, C, Go, Y, Kiyosue, A, Higashi, Y, Tokunaga, T, Kawasaki, T, Sakagami, S, Namba, S, Saku, K, Oku, K, Arakawa, T, Iida, H, Nakamura, Y, Yamamoto, K, Hata, Y, Katsuda, Y, Koga, Y, Shimizu, M, Uehara, H, Kajiyama, S, Okamoto, H, Shinozaki, T, Fujino, Y, Funazaki, T, Higa, N, Kaigawa, K, Koike, A, Nakane, H, Sato, K, Satoh, Y, Shirasawa, K, Sugino, H, Tanabe, J, Uemura, O, Yoshimichi, G, Akai, A, Himeno, H, Inage, T, Inoko, M, Kadokami, T, Noguchi, Y, Yamashita, K, Yasumura, Y, Yuge, M, Hosokawa, S, Kawamitsu, K, Kozuma, K, Matsuo, H, Nakashima, E, Okada, M, Wada, A, Yokoya, K, Iwade, K, Kawabata, K, Tanno, H, Ako, J, Fujita, H, Izumiya, Y, Kanno, M, Nunohiro, T, Ohmura, H, Ueno, T, Kakurina, N, Jasinkevica, I, Stukena, I, Veze, I, Eglite, R, Teterovska, D, Sime, I, Strazdiene, V, Venceviciene, L, Gustiene, O, Radzeviciene-Jurgute, R, Kucinskiene, A, Maskon, O, Lee, C, Erng, T, Gan, H, Mohamed Yusof, A, Ramanathan, G, Liew, H, Lopez Alvarado, A, Nevarez Ruiz, L, De los Rios Ibarra, M, Bazzoni Ruiz, A, Ramos Lopez, G, Llamas Esperon, G, De la Pena Topete, G, Violante Ortiz, R, Illescas Diaz, J, Leon Gonzalez, S, Sanchez Diaz, C, Mendez Machado, G, Venegas Carrillo, L, Aldrete Velasco, J, Cardona Munoz, E, Leiva Pons, J, Perez Alva, J, van der Zwaan, C, Oomen, A, van de Wal, R, Magro, M, Boswijk, D, Janus, C, Groutars, R, Tonino, W, Cornel, J, Oude Ophuis, A, Troquay, R, Liem, A, Westendorp, I, Van Hessen, M, Lok, D, De Nooijer, C, Den Hartog, F, Van Beek, E, Bendermacher, P, Jansen, R, Romer, T, Rensing, B, Hersbach, F, Herrman, J, Ladyjanskaia, G, Karalis, I, Linssen, G, Bokern, M, Visman, A, Kooij, A, Monajemi, H, Lieverse, A, Baker, J, Tie, S, Risberg, K, Hysing, J, Hoivik, H, Norheim, P, Solnor, L, Hovland, A, Kjaernli, T, Jocson, G, Coching, R, Batalla, E, Go, A, Habaluyas, R, Barcinas, R, Sy, R, Estepar, R, Germar, A, Trebacz, J, Szymkowiak, K, Wnetrzak-Michalska, R, Kopaczewski, J, Przekwas-Jaruchowska, M, Kania, G, Zabowka, M, Mirek-Bryniarska, E, Dabrowska, M, Napora, P, Konieczny, M, Spyra, J, Lysek, R, Pijanowski, Z, Grzegorzewski, B, Bednarkiewicz, Z, Kinasz, L, Antkowiak-Piatyszek, K, Stania, K, Szpajer, M, Staneta, P, Skonieczny, G, Ksiezycka-Majczynska, E, Blicharski, T, Piepiorka, M, Wozakowska-Kaplon, B, Zechowicz, T, Ilkowski, J, Lubiszewska, B, Hiczkiewicz, J, Wierzbicka, K, Kosior, D, Garbocz, P, Kubica, J, Raczak, G, Wozniak, I, Cygler, J, Kramarczuk, E, Bystryk, L, Pentela-Nowicka, J, Dabrowski, M, Podolec, P, Zieba, B, Mosiewicz, J, Dubaniewicz, W, Banach, M, Tyszecka, G, Lepich, T, Rychlewska-Hanczewska, A, Guzik, T, Monteiro, P, Pereira, H, Oliveira, L, Matos, P, Soares Goncalves, S, Leitao, A, Vasco Salgado, A, Timoteo, A, Pintilei, E, Badila, E, Militaru, C, Tudoran, M, Arsenescu-Georgescu, C, Mitu, F, Zdrenghea, D, Lighezan, D, Teodorescu, I, Popescu, M, Coman, I, Vintila, M, Vishnevsky, A, Lukyanov, Y, Blokhin, A, Kostenko, V, Shvarts, Y, Markov, V, Motylev, I, Dronov, D, Sherenkov, A, Barbarash, O, Shutemova, E, Bolshakova, O, Kobalava, Z, Voevoda, M, Treshkur, T, Zrazhevskiy, K, Pimenov, L, Solovev, O, Tarasov, N, Arkhipov, M, Freidlin, M, Shalaev, S, Yakhontova, P, Shustov, S, Goloshchekin, B, Panov, A, Bart, B, Bubnova, M, Gordeev, I, Osipova, I, Tereshenko, S, Solovieva, E, Meshkov, A, Zateyshchikov, D, Tan, J, Subramaniam, T, Pella, D, Fulop, P, Antalik, L, Dzupina, A, Banikova, A, Sosovec, D, Urgeova, L, Mazur, J, Hranai, M, Banik, M, Vinanska, D, Lennerova, J, Kovar, F, Pastrnakova, E, Uhliar, R, Blasko, P, Gonsorcik, J, Lukacova, J, Oriesek, R, Hatalova, K, du Toit, M, Ebrahim, I, Vawda, G, Lipschitz, S, Blignaut, S, Engelbrecht, J, Coetzer, T, Pretorius, M, Urbach, D, Badat, A, Pillay, S, Van Zyl, L, Abelson, M, van der Walt, E, Moodley, R, Jacovides, A, Oosthuysen, W, Klug, E, Lottering, H, Kok, J, Saaiman, J, Dawood, S, De Jong, D, Kapp, C, Makotoko, E, Bayat, J, Sarvan, M, Vally, T, Stapelberg, A, Kim, M, Bae, J, Cho, Y, Kim, S, Han, K, Her, S, Kim, B, Lee, S, Hong, B, Kim, W, Rha, S, Jeong, M, Shin, G, Vida Gutierrez, M, Valdes Chavarri, M, Pinto Sala, X, Gonzalez Juanatey, J, Civeira Murillo, F, Zamorano Gomez, J, Lekuona Goya, I, Iniguez Romo, A, Cordero Fort, A, Ascaso Gimilio, J, Millan Nunez-Cortes, J, Lindholm, C, Soderberg, S, Suutari, A, Berglund, S, Mooe, T, Kusiak, D, Bandh, S, Dahlen, G, Olsson, S, Witt, N, Tyden, P, Johansson, P, Cizinsky, S, Falck, G, Pettersson, S, Rasmanis, G, Ostergren, J, Moccetti, T, Beer, H, Eberli, F, Krahenbuhl, S, Linka, A, Ackermann, D, Michel, P, Yeh, H, Tsai, C, Wu, C, Hsia, C, Juang, J, Hsieh, I, Lai, W, Huang, C, Hsieh, Y, Sahin, T, Duzenli, M, Yigit, Z, Demir, M, Yilmaz, M, Muderrisoglu, I, Kirma, C, Ercan, E, Kayikcioglu, L, Balbay, Y, Lymar, I, Kulynych, O, Prokhorov, O, Karpenko, O, Kraіz, I, Vakaliuk, I, Stanislavchuk, M, Korzh, O, Rudyk, I, Zhurba, S, Svishchenko, Y, Tseluyko, V, Gyrina, O, Reshotko, D, Kopytsya, M, Volkov, V, Myshanych, G, Rebrov, B, Rishko, M, Rudenko, L, Shatylo, V, Parkhomenko, O, Yena, L, Golovchenko, O, Sorokina, I, Malynovsky, Y, Ivan, P, Blagden, M, Dear, H, Mathew, A, Lagocki, S, Kondagunta, V, Ahsan, A, Mckinnon, C, Douglas, F, Thom, S, Fiore, G, Caulfield, M, Lynch, M, Thomas, H, Bain, S, Hall, A, Mcnally, D, Fisher, M, Keeling, P, Al-Bahrani, A, Lip, G, Ellery, A, Purohit, J, Travill, C, Cappuccio, F, Davis, G, Gaunt, R, Adlam, D, Asamoah, N, Jaafar, F, Mccormack, T, Jupp, B, Pye, M, Ainsworth, P, Chauhan, A, Paul, N, Fairlie, H, Fox, C, Muzulu, S, Trevelyan, J, Aggarwal, R, Issa, B, Saravanan, P, Cruickshank, K, Gorog, D, Heller, S, Newby, D, Nicolson, A, Hare, P, Donnelly, P, Rutherfurd, S, de Belder, M, Finlayson, J, Harvey, J, Hoye, A, Kingston, D, Sarkar, D, Negahban, A, Webster, J, Wyatt, N, Muir, S, Cummings, M, Mackenzie, I, Senior, R, Capps, N, Fotherby, K, Mcintyre, H, Aldegather, J, Dixon, L, Saksena, R, Butler, R, Ramstad, D, Pierpont, B, Levinson, D, Mohammed, A, Haddad, T, Goel, A, Dave, K, Haught, W, Desire, A, Hershon, K, Napoli, M, Tami, L, Rothschild, R, Khurana, S, Gupta, D, Cheung, D, Hearne, S, Grubb, S, Miller, A, Baird, I, Marcus, A, Srivastava, S, Forgosh, L, Fritz, R, Mays, M, Bertolet, B, Reddy, J, Khan, M, Nakhle, S, Dill, S, Fishbein, G, Khan, B, Marais, H, Reschak, M, Malone, M, Nadar, V, Whitney, R, Reichman, A, Reyes, H, El Shahawy, M, Rabinowitz, A, Weinstein, D, Farhat, N, Onyema, D, Potu, R, Runquist, L, Barnum, O, Crater, T, Fialkow, J, Shah, A, Thompson, C, Wiseman, A, Doyle, T, Henderson, D, Herzog, W, Schnitzler, R, Carr, K, Davis, M, Nagajothi, N, Olsen, S, Rogers, W, Rubino, J, Singh, I, Tarleton, G, Bhagwat, R, Clardy, D, Jardula, M, Robinson, J, Torres, M, Vijay, N, Farris, N, Lillo, J, Moriarty, P, Recknor, C, Berlacher, P, Christensen, T, Gabra, N, Issa, M, Janik, M, Lawless, A, Molter, D, Stout, E, Brezina, B, Claxton, E, Linsky, R, Poock, J, Remler, R, Roseman, H, Schramm, E, Al-Joundi, T, Amin, J, Hitchcock, J, Isserman, S, Kirstein, J, Rider, J, Shalek, M, Sherman, H, Bernstein, M, Chandra, L, Hatharasinghe, R, Ibrahim, H, Iteld, B, Linzmeyer, K, Seaton, B, Zeig, S, Christofides, E, Dunbar, R, Griffin, S, Kohli, N, Koren, M, Pharr, W, Purdy, D, Spencer, R, Yeoman, G, Banerjee, S, Cheek, H, Engel, E, Hamroff, G, Huling, R, Kozlowski, L, Levin, P, Makam, S, Meengs, M, Bhushan, R, Erickson, B, Herman, L, Lo, E, Mcdowell, E, Mcgrew, F, Miller, M, Ord, J, Webel, R, Wilhoit, G, Wise, J, Yang, E, Budoff, M, Collins, J, Dauber, I, Dobkin, L, Focil, A, Gandy, W, Pasquini, J, Ramos, M, Rodriguez, D, Rosenson, R, Sanford, K, Schlau, A, Snyder, B, Stonesifer, L, Tang, A, De Souza, J, Elam, M, French, J, Guyton, J, Hage Korban, E, Kereiakes, D, King, M, Loh, I, Navarro, J, Simons, R, Tobin, T, Younis, L, Aboufakher, R, Baldari, D, Ballantyne, C, Broughton, R, Eaton, C, Johnston, J, Simon, W, Thomson, S, Vora, K, Youngman, D, Alzohaili, O, Auerbach, E, Brown, C, Burrough, B, Chen, Y, Gilpatrick, M, Landzberg, J, Mitchell, C, Rice, L, Rubenfire, M, Sofley, C, Strobl, D, Atassi, K, Davila, W, Diogo, J, Fagan, T, Joffe, I, Krishna, J, Osea, E, Penny, W, Rowe, W, Shapiro, M, Welker, J, Benton, R, Dobratz, D, Fortuin, F, Graham, J, Henry, B, Kusnick, B, Lutskiy, M, Mcrae, A, Saway, W, Scott, J, Shah, M, Weinberg, B, Zarich, S, Acheatel, R, Case, C, Earl, J, Fernandez, S, Giugliano, G, Handelsman, Y, Hermany, P, Holder, S, Kashyap, M, Khan, A, Lader, E, Peniston, J, Raoof, T, Sacco, J, Shore, K, Spriggs, D, Stringam, S, Tahirkheli, N, Delgado, E, Derian, W, Greenwald, J, Harris, M, Jackson, R, Marhefka, G, Mcelveen, W, Mooss, A, Morris, P, Murray, J, Pearlstein, P, Raisinghani, A, Rezkalla, S, Sakhrani, L, Schreibman, D, Shaoulian, E, Steinsapir, J, Yataco, A, De La Cruz, A, Fredrick, M, Goldenberg, E, Lee, D, Mccullum, K, Mclellan, B, Stephens, L, Wilson, S, Alfieri, A, Mandviwala, M, Orourke, D, Samal, A, Schmedtje, J, Waxman, F, Carhart, R, Clements, B, Dyke, C, Ghali, J, Gruberg, L, Hack, T, Jehle, A, Pogue, B, Schooley, C, and Shifrin, G
- Subjects
Male ,STATIN THERAPY ,2700 General Medicine ,Disease ,Cardiovascular ,PLACEBO-CONTROLLED TRIAL ,Gastroenterology ,0302 clinical medicine ,Anticholesteremic Agent ,Medicine ,Myocardial infarction ,11 Medical and Health Sciences ,ddc:616 ,Incidence ,Antibodies, Monoclonal ,General Medicine ,Cholesterol ,Cardiovascular Diseases ,Monoclonal ,Drug Therapy, Combination ,Proprotein Convertase 9 ,Antibody ,Aged ,Anticholesteremic Agents ,Atherosclerosis ,Cholesterol, LDL ,Double-Blind Method ,Female ,Follow-Up Studies ,Humans ,Hydroxymethylglutaryl-CoA Reductase Inhibitors ,Hypercholesterolemia ,Least-Squares Analysis ,Middle Aged ,Medicine (all) ,REDUCING LIPIDS ,Human ,medicine.medical_specialty ,Evinacumab ,Clinical Trials and Supportive Activities ,PCSK9 INHIBITION ,Follow-Up Studie ,LDL ,03 medical and health sciences ,Drug Therapy ,Clinical Research ,LDL-C ,Least-Squares Analysi ,Science & Technology ,Unstable angina ,PCSK9 ,medicine.disease ,chemistry ,Clinical Biochemistry ,030204 cardiovascular system & hematology ,Bococizumab ,FOURIER Steering Committee and Investigators ,Medical and Health Sciences ,chemistry.chemical_compound ,Antibodies monoclonal ,Cardiovascular Disease ,030212 general & internal medicine ,Stroke ,Humanized ,RISK ,biology ,PCSK9 Inhibitors ,10051 Rheumatology Clinic and Institute of Physical Medicine ,Heart Disease ,Atherosclerosi ,6.1 Pharmaceuticals ,Combination ,Cardiology ,Life Sciences & Biomedicine ,Antibodies, Monoclonal, Humanized ,EZETIMIBE ,610 Medicine & health ,Antibodies ,Medicine, General & Internal ,General & Internal Medicine ,Internal medicine ,CORONARY-HEART-DISEASE ,In patient ,Heart Disease - Coronary Heart Disease ,Alirocumab ,Ldl cholesterol ,business.industry ,Evaluation of treatments and therapeutic interventions ,Evolocumab ,Good Health and Well Being ,Settore MED/11 - MALATTIE DELL'APPARATO CARDIOVASCOLARE ,biology.protein ,MODERATE ,Hydroxymethylglutaryl-CoA Reductase Inhibitor ,business - Abstract
Background Evolocumab is a monoclonal antibody that inhibits proprotein convertase subtilisin–kexin type 9 (PCSK9) and lowers low-density lipoprotein (LDL) cholesterol levels by approximately 60%. Whether it prevents cardiovascular events is uncertain. Methods We conducted a randomized, double-blind, placebo-controlled trial involving 27,564 patients with atherosclerotic cardiovascular disease and LDL cholesterol levels of 70 mg per deciliter (1.8 mmol per liter) or higher who were receiving statin therapy. Patients were randomly assigned to receive evolocumab (either 140 mg every 2 weeks or 420 mg monthly) or matching placebo as subcutaneous injections. The primary efficacy end point was the composite of cardiovascular death, myocardial infarction, stroke, hospitalization for unstable angina, or coronary revascularization. The key secondary efficacy end point was the composite of cardiovascular death, myocardial infarction, or stroke. The median duration of follow-up was 2.2 years. Results At 48 weeks, the least-squares mean percentage reduction in LDL cholesterol levels with evolocumab, as compared with placebo, was 59%, from a median baseline value of 92 mg per deciliter (2.4 mmol per liter) to 30 mg per deciliter (0.78 mmol per liter) (P
- Published
- 2017
164. The Effect of Semaglutide on Mortality and COVID-19-Related Deaths: An Analysis From the SELECT Trial.
- Author
-
Scirica BM, Lincoff AM, Lingvay I, Bogdanski P, Buscemi S, Colhoun H, Craciun AE, Ezhov M, Hardt-Lindberg S, Kleist Jeppesen O, Matos ALSA, Node K, Schiele F, Toplak H, van Beek A, Weeke PE, Wiviott SD, Deanfield J, and Ryan D
- Subjects
- Humans, Male, Female, Middle Aged, Aged, Cause of Death trends, Hypoglycemic Agents therapeutic use, COVID-19 Drug Treatment, Overweight drug therapy, SARS-CoV-2, Double-Blind Method, COVID-19 mortality, Glucagon-Like Peptides therapeutic use, Obesity complications, Obesity mortality, Cardiovascular Diseases mortality, Cardiovascular Diseases prevention & control
- Abstract
Background: Patients with overweight and obesity are at increased risk of death from multiple causes, including cardiovascular (CV) death, with few therapies proven to reduce the risk., Objectives: This study sought to assess the effect of semaglutide 2.4 mg on all-cause death, CV death, and non-CV death, including subcategories of death and death from coronavirus disease-2019 (COVID-19)., Methods: The SELECT (Semaglutide Effects on Cardiovascular Outcomes in Patients With Overweight or Obesity) trial randomized 17,604 participants ≥45 years of age with a body mass index ≥27 kg/m
2 with established CV disease but without diabetes to once-weekly subcutaneous semaglutide 2.4 mg or placebo; the mean trial duration was 3.3 years. Adjudicated causes of all deaths, COVID-19 cases, and associated deaths were captured prospectively., Results: Of 833 deaths, 485 (58%) were CV deaths, and 348 (42%) were non-CV deaths. Participants assigned to semaglutide vs placebo had lower rates of all-cause death (HR: 0.81; 95% CI: 0.71-0.93), CV death (HR: 0.85; 95% CI: 0.71-1.01), and non-CV death (HR: 0.77; 95% CI: 0.62-0.95). The most common causes of CV death with semaglutide vs placebo were sudden cardiac death (98 vs 109; HR: 0.89; 95% CI: 0.68-1.17) and undetermined death (77 vs 90; HR: 0.85; 95% CI: 0.63-1.15). Infection was the most common cause of non-CV death and occurred at a lower rate in the semaglutide vs the placebo group (62 vs 87; HR: 0.71; 95% CI: 0.51-0.98). Semaglutide did not reduce incident COVID-19; however, among participants who developed COVID-19, fewer participants treated with semaglutide had COVID-19-related serious adverse events (232 vs 277; P = 0.04) or died of COVID-19 (43 vs 65; HR: 0.66; 95% CI: 0.44-0.96). High rates of infectious deaths occurred during the COVID-19 pandemic, with less infectious death in the semaglutide arm, and resulted in fewer participants in the placebo group being at risk for CV death., Conclusions: Compared to placebo, patients treated with semaglutide 2.4 mg had lower rates of all-cause death, driven similarly by CV and non-CV death. The lower rate of non-CV death with semaglutide was predominantly because of fewer infectious deaths. These findings highlight the effect of semaglutide on mortality across a broad population of patients with CV disease and obesity. (Semaglutide Effects on Cardiovascular Outcomes in Patients With Overweight or Obesity [SELECT]; NCT03574597)., Competing Interests: Funding Support and Author Disclosures Dr Scirica has received institutional research grants to Brigham and Women’s Hospital from Better Therapeutics, Merck, Novo Nordisk, and Pfizer; has received consulting fees from Allergan, Amgen, Boehringer Ingelheim, Better Therapeutics, Elsevier Practice Update Cardiology, Esperion, Hanmi, Lexicon, and Novo Nordisk; and holds equity in Health [at] Scale and Doximity. Dr Lincoff has received research grants from AbbVie Inc, AstraZeneca, CSL Behring, Eli Lilly and Company, Esperion Therapeutics, Inc, and Novartis paid to his institution; and has served as a consultant for Akebia Therapeutics Inc, Alnylam Pharmaceuticals Inc, Ardelyx, Eli Lilly and Company, FibroGen, GlaxoSmithKline, Intarcia, Medtronic Vascular Inc, Novartis Pharmaceuticals Corporation, Novo Nordisk, Provention Bio, Entity, and ReCor Medical. Dr Lingvay has received research grants from Boehringer Ingelheim, Merck, Mylan Pharmaceuticals Inc, Novo Nordisk, Pfizer, and Sanofi US Services Inc; has served as a consultant for AstraZeneca, Bayer Healthcare Pharmaceuticals Inc, Biomea, Boehringer Ingelheim, Carmot, Eli Lilly and Company, Intarcia, Intercept Pharmaceuticals, Inc, Janssen Global Services, LLC, Johnson & Johnson Medical Devices & Diagnostics Group-Latin America, LLC, MannKind Corporation, Merck, Novo Nordisk, Pfizer Inc, Sanofi US Services Inc, Shionogi Inc, Structure Therapeutics, Target Pharma, Valeritas, Inc, and Zealand Pharma; and has received travel expenses from Boehringer Ingelheim, Eli Lilly and Company, Johnson & Johnson Medical Devices & Diagnostics Group-Latin America, LLC, Novo Nordisk, Sanofi US Services Inc, and Zealand Pharma A/S. Dr Buscemi has received advisory/consulting honoraria from Novo Nordisk, Eli Lilly, Pfizer, Boehringer Ingelheim, and Dompè. Dr Colhoun has served on advisory panels for Novo Nordisk and Bayer; has received research funding from Sanofi, Roche, and IQVIA; has received grants from Chief Scientist Office, Diabetes UK, European Commission, Juvenile Diabetes Research Foundation, and Medical Research Council; has served on the Speakers Bureau for Novo Nordisk; and holds equity in Roche Pharmaceuticals and Bayer. Dr Craciun has received advisory/consulting fees and/or other support from Novo Nordisk, Eli Lilly, Sanofi, Boehringer Ingelheim, Servier, Berlin Chemie, and Viatris. Dr Hardt-Lindberg is an employee of and stakeholder in Novo Nordisk. Dr Jeppesen is an employee of and stakeholder in Novo Nordisk. Dr Matos is an employee of and stakeholder in Novo Nordisk. Dr Node has received honoraria from AstraZeneca, Bayer Yakuhin, Boehringer Ingelheim Japan, Daiichi-Sankyo, Eli Lilly Japan, Mitsubishi Tanabe Pharma, Merck Sharp & Dohme, Novartis Pharma, and Otsuka; has received research grants from Astellas, Bayer Yakuhin, Boehringer Ingelheim Japan, Fujiyakuhin, Mitsubishi Tanabe Pharma, Mochida Pharmaceutical, and Novartis Pharma; and has received scholarships from Abbott, Boehringer Ingelheim Japan, Daiichi-Sankyo, Mitsubishi Tanabe Pharma, and Teijin Pharma. Dr Toplak has received institutional research grants from Amgen, Daiichi-Sankyo, Novo Nordisk, and Novartis; and has received consulting/speaker honoraria from Amgen, Daiichi-Sankyo, Novartis, and Novo Nordisk. Dr van Beek has been contracted via the University of Groningen (no personal payment) to undertake consultancy for Novo Nordisk, Eli Lilly, and Boehringer Ingelheim. Dr Weeke is an employee of and stakeholder in Novo Nordisk. Dr Wiviott has received research grants from Amgen, AstraZeneca, Janssen, Merck, and Pfizer; has received consulting fees from Icon, Novo Nordisk, and Verian; has received speaking honoraria from Harvard Medical School; is a member of the TIMI Study Group, which has received institutional research grant support through Brigham and Women’s Hospital from Abbott, Amgen, Anthos Therapeutics, ARCA Biopharma, Inc, AstraZeneca, Bayer HealthCare Pharmaceuticals, Inc, Daiichi-Sankyo, Eisai, Intarcia, Ionis Pharmaceuticals, Inc, Janssen Research and Development, LLC, MedImmune, Merck, Novartis, Pfizer, Quark Pharmaceuticals, Regeneron Pharmaceuticals, Inc, Roche, Siemens Healthcare Diagnostics, Inc, Softcell Medical Limited, The Medicines Company, and Zora Biosciences; and his spouse, Dr Caroline Fox, is a former employee of Merck, Flagship Labs, and current employee of Vertex. Dr Deanfield has received consulting honoraria from Amgen, Boehringer Ingelheim, Merck, Pfizer, Aegerion, Novartis, Sanofi, Takeda, Novo Nordisk, and Bayer; and has received research grants from British Heart Foundation, MRC(UK), National Institute for Health and Care Research, PHE, Merck Sharp & Dohme, Pfizer, Aegerion, Colgate, and Roche. Dr Ryan has received consulting honoraria from Altimmune, Amgen, Biohaven, Boehringer Ingelheim, Calibrate, Carmot Therapeutics, CinRx, Eli Lilly, Epitomee, Gila Therapeutics, Ifa Celtic, Novo Nordisk, Pfizer, Rhythm, Scientific Intake, Wondr Health, and Zealand; and has received stock options from Calibrate, Epitomee, Scientific Intake, and Xeno Bioscience. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)- Published
- 2024
- Full Text
- View/download PDF
165. [A clinical case of reverse left ventricular remodeling in patient with pathogenic TTN mutation. Case report].
- Author
-
Nasonova SN, Meshkov AN, Zhirov IV, Osmolovskaya YF, Shoshina AA, Gagloev AV, Dzhumaniiazova IH, Zelenova EA, Erema VV, Gusakova MS, Ivanov MV, Terekhov MV, Kashtanova DA, Nekrasova AI, Mitrofanov SI, Shingaliev AS, Yudin VS, Keskinov AA, Gomyranova NV, Chubykina UV, Ezhov MV, Tereshchenko SN, Yudin SM, and Boytsov SA
- Subjects
- Humans, Mutation, Male, Adult, Echocardiography methods, Connectin genetics, Cardiomyopathy, Dilated genetics, Cardiomyopathy, Dilated physiopathology, Cardiomyopathy, Dilated diagnosis, Ventricular Remodeling genetics, Ventricular Remodeling physiology
- Abstract
Dilated cardiomyopathy (DCM) is a leading cause of heart failure, sudden cardiac death, and heart transplantation in young patients. The causes of DCM are varied and include genetic factors and metabolic, infectious, toxic and others factors. Today it is known that germline mutations in more than 98 genes can be associated with the occurrence of DCM. However, the penetrance of these genes often depends on a combination of factors, including modifiable ones, i.e. those that change under the influence of the environment. About 20-25% of genetically determined forms of DCM are due to mutations in the titin gene ( TTN ). Titin is the largest protein in the body, which is an important component of the sarcomer. Although titin is the largest protein in the human body, its role in the physiology of heart and disease is not yet fully understood. However, a mutation in the TTN gene may later represent a potential therapeutic target for genetic and acquired cardiomyopathy. Thus, the analysis of clinical cases of cardiomyopathy in patients with identified mutations in the TTN gene is of great scientific interest. The article presents a clinical case of manifestation of DCM in patient with a revealed pathogenic variant of mutation in the gene TTN and reverse left ventricular remodeling of the against the background of optimal therapy of heart failure in a subsequent outpatient observation.
- Published
- 2024
- Full Text
- View/download PDF
166. Blood pressure measurement and assessment of arterial structure and function: an expert group position paper.
- Author
-
Asmar R, Stergiou G, de la Sierra A, Jelaković B, Millasseau S, Topouchian J, Shirai K, Blacher J, Avolio A, Jankowski P, Parati G, Bilo G, Rewiuk K, Mintale I, Rajzer M, Agabiti-Rosei E, Ince C, Postadzhiyan A, Zimlichman R, Struijker-Boudier H, Benetos A, Bäck M, Tasic N, Sirenko Y, Zelveian P, Wang H, Fantin F, Kotovskaya Y, Ezhov M, and Kotsis V
- Subjects
- Humans, Hemodynamics physiology, Blood Pressure Determination methods, Arteries physiology, Blood Pressure physiology
- Abstract
Measuring blood pressure (BP) and investigating arterial hemodynamics are essential in understanding cardiovascular disease and assessing cardiovascular risk. Several methods are used to measure BP in the doctor's office, at home, or over 24 h under ambulatory conditions. Similarly, several noninvasive methods have been introduced for assessing arterial structure and function; these methods differ for the large arteries, the small ones, and the capillaries. Consequently, when studying arterial hemodynamics, the clinician is faced with a multitude of assessment methods whose technical details, advantages, and limitations are sometimes unclear. Moreover, the conditions and procedures for their optimal implementation, and/or the reference normality values for the parameters they yield are not always taken into sufficient consideration. Therefore, a practice guideline summarizing the main methods and their use in clinical practice is needed. This expert group position paper was developed by an international group of scientists after a two-day meeting during which each of the most used methods and techniques for blood pressure measurement and arterial function and structure evaluation were presented and discussed, focusing on their advantages, limitations, indications, normal values, and their pragmatic clinical application., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)
- Published
- 2024
- Full Text
- View/download PDF
167. Validation of artificial intelligence application for dental caries diagnosis on intraoral bitewing and periapical radiographs.
- Author
-
Szabó V, Szabó BT, Orhan K, Veres DS, Manulis D, Ezhov M, and Sanders A
- Subjects
- Humans, Reproducibility of Results, Radiography, Dental methods, Male, Adult, Female, Dental Caries diagnostic imaging, Radiography, Bitewing, Artificial Intelligence, Neural Networks, Computer, Sensitivity and Specificity
- Abstract
Objectives: This study aimed to assess the reliability of AI-based system that assists the healthcare processes in the diagnosis of caries on intraoral radiographs., Methods: The proximal surfaces of the 323 selected teeth on the intraoral radiographs were evaluated by two independent observers using an AI-based (Diagnocat) system. The presence or absence of carious lesions was recorded during Phase 1. After 4 months, the AI-aided human observers evaluated the same radiographs (Phase 2), and the advanced convolutional neural network (CNN) reassessed the radiographic data (Phase 3). Subsequently, data reflecting human disagreements were excluded (Phase 4). For each phase, the Cohen and Fleiss kappa values, as well as the sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy of Diagnocat, were calculated., Results: During the four phases, the range of Cohen kappa values between the human observers and Diagnocat were κ=0.66-1, κ=0.58-0.7, and κ=0.49-0.7. The Fleiss kappa values were κ=0.57-0.8. The sensitivity, specificity and diagnostic accuracy values ranged between 0.51-0.76, 0.88-0.97 and 0.76-0.86, respectively., Conclusions: The Diagnocat CNN supports the evaluation of intraoral radiographs for caries diagnosis, as determined by consensus between human and AI system observers., Clinical Significance: Our study may aid in the understanding of deep learning-based systems developed for dental imaging modalities for dentists and contribute to expanding the body of results in the field of AI-supported dental radiology.., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: David Manulis, Matyey Ezhov and Alex Sanders are employees of Diagnocat Co. Ltd.. Kaan Orhan is a scientific research advisor for the Diagnocat Co. Ltd., San Francisco CA., (Copyright © 2024. Published by Elsevier Ltd.)
- Published
- 2024
- Full Text
- View/download PDF
168. Evaluation of a Decision Support System Developed with Deep Learning Approach for Detecting Dental Caries with Cone-Beam Computed Tomography Imaging.
- Author
-
Amasya H, Alkhader M, Serindere G, Futyma-Gąbka K, Aktuna Belgin C, Gusarev M, Ezhov M, Różyło-Kalinowska I, Önder M, Sanders A, Costa ALF, Castro Lopes SLP, and Orhan K
- Abstract
This study aims to investigate the effect of using an artificial intelligence (AI) system (Diagnocat, Inc., San Francisco, CA, USA) for caries detection by comparing cone-beam computed tomography (CBCT) evaluation results with and without the software. 500 CBCT volumes are scored by three dentomaxillofacial radiologists for the presence of caries separately on a five-point confidence scale without and with the aid of the AI system. After visual evaluation, the deep convolutional neural network (CNN) model generated a radiological report and observers scored again using AI interface. The ground truth was determined by a hybrid approach. Intra- and inter-observer agreements are evaluated with sensitivity, specificity, accuracy, and kappa statistics. A total of 6008 surfaces are determined as 'presence of caries' and 13,928 surfaces are determined as 'absence of caries' for ground truth. The area under the ROC curve of observer 1, 2, and 3 are found to be 0.855/0.920, 0.863/0.917, and 0.747/0.903, respectively (unaided/aided). Fleiss Kappa coefficients are changed from 0.325 to 0.468, and the best accuracy (0.939) is achieved with the aided results. The radiographic evaluations performed with aid of the AI system are found to be more compatible and accurate than unaided evaluations in the detection of dental caries with CBCT images.
- Published
- 2023
- Full Text
- View/download PDF
169. [Association of cardiovascular disease with hospital mortality in COVID-19 patients].
- Author
-
Pogosova NV, Ezhov MV, Barinova IV, Ausheva AK, Kuchiev DT, Popova AB, Arutyunov AA, and Boytsov SA
- Subjects
- Male, Humans, Female, Aged, 80 and over, Hospital Mortality, Risk Factors, Cardiovascular Diseases complications, COVID-19 complications, Heart Failure complications, Myocardial Infarction complications
- Abstract
Aim: To evaluate the relationship between the in-hospital mortality of patients with COVID-19 and the history of cardiovascular disease (CVD) using data from the Russian registry of patients with COVID-19., Material and Methods: This study included 758 patients with COVID-19 (403 men, 355 women) aged from 18 to 95 years (median, 61 years), successively hospitalized in the COVID hospital of the Chazov National Medical Research Center of Cardiology from April through June 2020. Death predictors were studied using single- and multivariate regression analyses with the SPSS Statistics, Version 23.0 software., Results: During the stay in the hospital, 59 (7.8 %) patients with COVID-19 died, 677 (89.3 %) were discharged, and 22 (2.9 %) were transferred to other hospitals. The univariate regression analysis showed that the increase in age per decade was associated with a 92% increase in the risk of death [relative risk (RR), 1.92; 95% confidence interval (CI), 1.58-2.34; p <0.001], and an increase in the number of CVDs increases the risk of death by 71% (RR 1.71; 95% CI 1.42-2.07; p<0.001). The presence of one or more CVDs or specific diseases [atrial fibrillation, chronic heart failure (CHF), ischemic heart disease, myocardial infarction, history of cerebrovascular accidents], as well as diabetes mellitus were associated with a higher risk of fatal outcome during the hospitalization for COVID-19. The presence of any CVD increased the risk of in-hospital death by 3.2 times. However, when the model was adjusted for age and sex, this association lost its strength, and only the presence of CHF was associated with a 3-fold increase in the risk of death (RR, 3.16; 95 % CI, 1.64-6.09; p=0.001). Age was another independent predictor of death (RR, 1.05; 95 % CI, 1.03-1.08; p < 0.001)., Conclusion: A history of CVD and the CVD number and severity are associated with a higher risk of death during the hospitalization for COVID-19; the independent predictors of in-hospital death are an age of 80 years and older and CHF.
- Published
- 2023
- Full Text
- View/download PDF
170. Assessing the reliability of CBCT-based AI-generated STL files in diagnosing osseous changes of the mandibular condyle: a comparative study with ground truth diagnosis.
- Author
-
Orhan K, Sanders A, Ünsal G, Ezhov M, Mısırlı M, Gusarev M, İçen M, Shamshiev M, Keser G, Namdar Pekiner F, Golitsyna M, Önder M, Manulis D, and Atakan C
- Subjects
- Humans, Mandibular Condyle diagnostic imaging, Retrospective Studies, Reproducibility of Results, Cone-Beam Computed Tomography methods, Temporomandibular Joint, Osteophyte diagnostic imaging, Osteophyte pathology, Spiral Cone-Beam Computed Tomography, Osteosclerosis diagnostic imaging
- Abstract
Objectives: This study aims to evaluate the reliability of AI-generated STL files in diagnosing osseous changes of the mandibular condyle and compare them to a ground truth (GT) diagnosis made by six radiologists., Methods: A total of 432 retrospective CBCT images from four universities were evaluated by six dentomaxillofacial radiologists who identified osseous changes such as flattening, erosion, osteophyte formation, bifid condyle formation, and osteosclerosis. All images were evaluated by each radiologist blindly and recorded on a spreadsheet. All evaluations were compared and for the disagreements, a consensus meeting was held online to create a uniform GT diagnosis spreadsheet. A web-based dental AI software was used to generate STL files of the CBCT images, which were then evaluated by two dentomaxillofacial radiologists. The new observer, GT, was compared to this new STL file evaluation, and the interclass correlation (ICC) value was calculated for each pathology., Results: Out of the 864 condyles assessed, the ground truth diagnosis identified 372 cases of flattening, 185 cases of erosion, 70 cases of osteophyte formation, 117 cases of osteosclerosis, and 15 cases of bifid condyle formation. The ICC values for flattening, erosion, osteophyte formation, osteosclerosis, and bifid condyle formation were 1.000, 0.782, 1.000, 0.000, and 1.000, respectively, when comparing diagnoses made using STL files with the ground truth., Conclusions: AI-generated STL files are reliable in diagnosing bifid condyle formation, osteophyte formation, and flattening of the condyle. However, the diagnosis of osteosclerosis using AI-generated STL files is not reliable, and the accuracy of diagnosis is affected by the erosion grade., Competing Interests: Conflict of interest statementAll authors declare that they have no conflict of interest.
- Published
- 2023
- Full Text
- View/download PDF
171. Non-HDL-cholesterol in dyslipidemia: Review of the state-of-the-art literature and outlook.
- Author
-
Raja V, Aguiar C, Alsayed N, Chibber YS, ElBadawi H, Ezhov M, Hermans MP, Pandey RC, Ray KK, Tokgözoglu L, Zambon A, Berrou JP, and Farnier M
- Subjects
- Humans, Middle Aged, Cholesterol, LDL, Cholesterol, HDL, Cholesterol, Lipoproteins, Risk Factors, Hydroxymethylglutaryl-CoA Reductase Inhibitors therapeutic use, Cardiovascular Diseases, Dyslipidemias diagnosis, Dyslipidemias drug therapy, Dyslipidemias epidemiology, Atherosclerosis diagnosis, Atherosclerosis epidemiology
- Abstract
Dyslipidemia refers to unhealthy changes in blood lipid composition and is a risk factor for atherosclerotic cardiovascular diseases (ASCVD). Usually, low-density lipoprotein-cholesterol (LDL-C) is the primary goal for dyslipidemia management. However, non-high-density lipoprotein cholesterol (non-HDL-C) has gained attention as an alternative, reliable goal. It encompasses all plasma lipoproteins like LDL, triglyceride-rich lipoproteins (TRL), TRL-remnants, and lipoprotein a [Lp(a)] except high-density lipoproteins (HDL). In addition to LDL-C, several other constituents of non-HDL-C have been reported to be atherogenic, aiding the pathophysiology of atherosclerosis. They are acknowledged as contributors to residual ASCVD risk that exists in patients on statin therapy with controlled LDL-C levels. Therefore, non-HDL-C is now considered an independent risk factor or predictor for CVD. The popularity of non-HDL-C is attributed to its ease of estimation and non-dependency on fasting status. It is also better at predicting ASCVD risk in patients on statin therapy, and/or in those with obesity, diabetes, and metabolic disorders. In addition, large follow-up studies have reported that individuals with higher baseline non-HDL-C at a younger age (<45 years) were more prone to adverse CVD events at an older age, suggesting a predictive ability of non-HDL-C over the long term. Consequently, non-HDL-C is recommended as a secondary goal for dyslipidemia management by most international guidelines. Intriguingly, geographical patterns in recent epidemiological studies showed remarkably high non-HDL-C attributable mortality in high-risk countries. This review highlights the independent role of non-HDL-C in ASCVD pathogenesis and prognosis. In addition, the need for a country-specific approach to dyslipidemia management at the community/population level is discussed. Overall, non-HDL-C can become a co-primary or primary goal in dyslipidemia management., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)
- Published
- 2023
- Full Text
- View/download PDF
172. Determining the reliability of diagnosis and treatment using artificial intelligence software with panoramic radiographs.
- Author
-
Orhan K, Aktuna Belgin C, Manulis D, Golitsyna M, Bayrak S, Aksoy S, Sanders A, Önder M, Ezhov M, Shamshiev M, Gusarev M, and Shlenskii V
- Abstract
Purpose: The objective of this study was to evaluate the accuracy and effectiveness of an artificial intelligence (AI) program in identifying dental conditions using panoramic radiographs (PRs), as well as to assess the appropriateness of its treatment recommendations., Material and Methods: PRs from 100 patients (representing 4497 teeth) with known clinical examination findings were randomly selected from a university database. Three dentomaxillofacial radiologists and the Diagnocat AI software evaluated these PRs. The evaluations were focused on various dental conditions and treatments, including canal filling, caries, cast post and core, dental calculus, fillings, furcation lesions, implants, lack of interproximal tooth contact, open margins, overhangs, periapical lesions, periodontal bone loss, short fillings, voids in root fillings, overfillings, pontics, root fragments, impacted teeth, artificial crowns, missing teeth, and healthy teeth., Results: The AI demonstrated almost perfect agreement (exceeding 0.81) in most of the assessments when compared to the ground truth. The sensitivity was very high (above 0.8) for the evaluation of healthy teeth, artificial crowns, dental calculus, missing teeth, fillings, lack of interproximal contact, periodontal bone loss, and implants. However, the sensitivity was low for the assessment of caries, periapical lesions, pontic voids in the root canal, and overhangs., Conclusion: Despite the limitations of this study, the synthesized data suggest that AI-based decision support systems can serve as a valuable tool in detecting dental conditions, when used with PR for clinical dental applications., Competing Interests: Conflicts of Interest: The authors have no disclosures to report regarding funding, disclaimer statements, presentations of the research at conferences or symposia, or postings of the work on a preprint server, website, or other location. Kaan Orhan serves as a Scientific Advisor for Diagnocat Inc., based in San Francisco, CA, USA., (Copyright © 2023 by Korean Academy of Oral and Maxillofacial Radiology.)
- Published
- 2023
- Full Text
- View/download PDF
173. World Heart Federation Cholesterol Roadmap 2022.
- Author
-
Ray KK, Ference BA, Séverin T, Blom D, Nicholls SJ, Shiba MH, Almahmeed W, Alonso R, Daccord M, Ezhov M, Olmo RF, Jankowski P, Lanas F, Mehta R, Puri R, Wong ND, Wood D, Zhao D, Gidding SS, Virani SS, Lloyd-Jones D, Pinto F, Perel P, and Santos RD
- Subjects
- Humans, Cholesterol, Lipoproteins therapeutic use, Apolipoproteins B therapeutic use, Hydroxymethylglutaryl-CoA Reductase Inhibitors therapeutic use, Dyslipidemias, Atherosclerosis diagnosis, Cardiovascular Diseases epidemiology, Cardiovascular Diseases prevention & control, Cardiovascular Diseases diagnosis
- Abstract
Background: Atherosclerotic cardiovascular diseases (ASCVD) including myocardial infarction, stroke and peripheral arterial disease continue to be major causes of premature death, disability and healthcare expenditure globally. Preventing the accumulation of cholesterol-containing atherogenic lipoproteins in the vessel wall is central to any healthcare strategy to prevent ASCVD. Advances in current concepts about reducing cumulative exposure to apolipoprotein B (apo B) cholesterol-containing lipoproteins and the emergence of novel therapies provide new opportunities to better prevent ASCVD. The present update of the World Heart Federation Cholesterol Roadmap provides a conceptual framework for the development of national policies and health systems approaches, so that potential roadblocks to cholesterol management and thus ASCVD prevention can be overcome., Methods: Through a review of published guidelines and research papers since 2017, and consultation with a committee composed of experts in clinical management of dyslipidaemias and health systems research in low-and-middle income countries (LMICs), this Roadmap identifies (1) key principles to effective ASCVD prevention (2) gaps in implementation of these interventions (knowledge-practice gaps); (3) health system roadblocks to treatment of elevated cholesterol in LMICs; and (4) potential strategies for overcoming these., Results: Reducing the future burden of ASCVD will require diverse approaches throughout the life-course. These include: a greater focus on primordial prevention; availability of affordable cholesterol testing; availability of universal cholesterol screening for inherited dyslipidaemias; risk stratification moving beyond 10-year risk to look at lifetime risk with adequate risk estimators; wider availability of affordable cholesterol-lowering therapies which should include statins as essential medications globally; use of adequate doses of potent statin regimens; and combination therapies with ezetimibe or other therapies in order to attain and maintain robust reductions in LDL-C in those at highest risk. Continuing efforts are needed on health literacy for both the public and healthcare providers, utilising multi-disciplinary teams in healthcare and applications that quantify both ASCVD risk and benefits of treatment as well as increased adherence to therapies., Conclusions: The adverse effects of LDL-cholesterol and apo B containing lipoprotein exposure are cumulative and result in ASCVD. These are preventable by implementation of different strategies, aimed at efficiently tackling atherosclerosis at different stages throughout the human life-course. Preventive strategies should therefore be updated to implement health policy, lifestyle changes and when needed pharmacotherapies earlier with investment in, and a shift in focus towards, early preventive strategies that preserve cardiovascular health rather than treat the consequences of ASCVD., Competing Interests: Kausik K. Ray has received honoraria for consulting, lectures from Kowa, Amgen, Regeneron Pharmaceuticals, Sanofi, Daiichi Sankyo, Pfizer, Viatris, AstraZeneca, Eli Lilly, Esperion, New Amsterdam Pharma, Novartis, Silence Therapeutics, Bayer, Boehringer Ingelheim, Novo Nordisk, SCRIBE, CRISPR, Cargene, Vaxxinity, Abbott, Resverlogix. In addition, he has received research grant support to his institution from Sanofi, Daiichi Sankyo, Amgen, Pfizer and MSD and support from the NIHR Imperial Biomedical Research Centre. Brian A. Ference has received research grants from Novartis, Amgen, Pfizer, Merck, and Esperion Therapeutics. In addition, the author has received personal fees for consulting, advisory board participation and lectures from Novartis, Amgen, Regeneron, Sanofi, Merck, Pfizer, Eli Lilly, Novo Nordisk, AstraZeneca, Viatris, The Medicines Co, Mylan, Daiichi Sankyo, dalCOR, CiVi Pharma, KrKa Phamaceuticals, the American College of Cardiology, the European Society of Cardiology, and the European Atherosclerosis Society. Dirk J. Blom has received research grants from Amgen, Amryt, AstraZeneca, IONIS, LIB Therapeutics, Novartis, Regeneron, Sanofi; Lecture fees and personal fees from Amgen, Novartis, Organon, Sandoz, Sanofi and has participated in advisory board for Amgen, Amryt (Chair of the LOWER study steering committee), and Sanofi. Stephen J. Nicolls has benefitted from research support from AstraZeneca, New Amsterdam Pharma, Amgen, Anthera, Eli Lilly, Esperion, Novartis, Cerenis, The Medicines Company, Resverlogix, InfraReDx, Roche, Sanofi-Regeneron and LipoScience and consulting and honoraria fees from AstraZeneca, Amarin, Akcea, Eli Lilly, Anthera, Omthera, Merck, Takeda, Resverlogix, Sanofi-Regeneron, CSL Behring, Esperion, Boehringer Ingelheim, Sequirus. Rodrigo Alonso has received honorary fees and participation in pharma symposia or advisory boards in the last five years from Amgen, Tecnofarma, SAVAL, ABBOTT, NovoNordisk, Boehringer-Ingelheim and Teva. Piotr Jankowski has received Honoraria and travel grants from Amgen, Sanofi, Servier. Roopa Mehta has been part of the speakers’ bureau for Amgen. Nathan D. Wong has received Research support through his institution from Novartis and Novo Nordisk and has been a consultant to Novartis. As Co-Principal Investigator of INTERASPIRE, David A. Wood’s Institute is in receipt of Independent Investigator Initiated grants from Abbott, Novartis, Pfizer, Sanofi, Viatris. Samuel S. Gidding has been a consultant on paediatric clinical trials of bempedoic acid for Esperion. Fausto J. Pinto has participated in Advisory Board, Speaker’s bureau, and clinical trials with Astra-Zeneca, Daichii Sankyo, Amgen, Sanofi. Raul D. Santos has received honoraria related to speaker activities, consulting or research from: Abbott, Ache, Abbott, Amgen, Astra Zeneca, Biolab, EMS, Hypera, Libbs, Esperion, Kowa, Getz pharma, Novo-Nordisk, Novartis, Merck, PTC therapeutics, Pfizer, and Sanofi., (Copyright: © 2022 The Author(s).)
- Published
- 2022
- Full Text
- View/download PDF
174. AI-based automatic segmentation of craniomaxillofacial anatomy from CBCT scans for automatic detection of pharyngeal airway evaluations in OSA patients.
- Author
-
Orhan K, Shamshiev M, Ezhov M, Plaksin A, Kurbanova A, Ünsal G, Gusarev M, Golitsyna M, Aksoy S, Mısırlı M, Rasmussen F, Shumilov E, and Sanders A
- Subjects
- Algorithms, Artificial Intelligence, Humans, Pharynx diagnostic imaging, Cone-Beam Computed Tomography methods, Spiral Cone-Beam Computed Tomography
- Abstract
This study aims to generate and also validate an automatic detection algorithm for pharyngeal airway on CBCT data using an AI software (Diagnocat) which will procure a measurement method. The second aim is to validate the newly developed artificial intelligence system in comparison to commercially available software for 3D CBCT evaluation. A Convolutional Neural Network-based machine learning algorithm was used for the segmentation of the pharyngeal airways in OSA and non-OSA patients. Radiologists used semi-automatic software to manually determine the airway and their measurements were compared with the AI. OSA patients were classified as minimal, mild, moderate, and severe groups, and the mean airway volumes of the groups were compared. The narrowest points of the airway (mm), the field of the airway (mm
2 ), and volume of the airway (cc) of both OSA and non-OSA patients were also compared. There was no statistically significant difference between the manual technique and Diagnocat measurements in all groups (p > 0.05). Inter-class correlation coefficients were 0.954 for manual and automatic segmentation, 0.956 for Diagnocat and automatic segmentation, 0.972 for Diagnocat and manual segmentation. Although there was no statistically significant difference in total airway volume measurements between the manual measurements, automatic measurements, and DC measurements in non-OSA and OSA patients, we evaluated the output images to understand why the mean value for the total airway was higher in DC measurement. It was seen that the DC algorithm also measures the epiglottis volume and the posterior nasal aperture volume due to the low soft-tissue contrast in CBCT images and that leads to higher values in airway volume measurement., (© 2022. The Author(s).)- Published
- 2022
- Full Text
- View/download PDF
175. [The relationship between the level of Lр(а) and the prevalence of atherosclerosis among young patients].
- Author
-
Klesareva EA, Afanasieva OI, Sherstyuk EE, Tmoyan NA, Razova OA, Tyurina AV, Afanasieva MI, Ezhov MV, and Pokrovsky SN
- Subjects
- Humans, Male, Middle Aged, Biomarkers, C-Reactive Protein, Lipoprotein(a), Prevalence, Risk Factors, Female, Adolescent, Young Adult, Adult, Atherosclerosis diagnosis, Atherosclerosis epidemiology, Atherosclerosis etiology, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Hyperlipoproteinemias
- Abstract
Background: Hyperlipoproteinemia (a) is an independent and cause risk factor for atherosclerotic cardiovascular diseases (ASCVD). The correlation between lipoprotein (a) Lp(a) and inflammation in the vessel wall was actively studied during the past few years. C-reactive protein (CRP) plays an important role in ASCVD., Aim: To analyze the relationship between hyperlipoproteinemia (a), inflammatory markers, and the early development of stenosing atherosclerosis (AS) in several vascular pools., Materials and Methods: 76 patients, 55 men aged 18 to 55 years and 21women 18 to 60 years, with the results of instrumental examination of coronary, carotid and lower extremities vascular pools were enrolled. Three groups: with stenosing (50%) AS of only one (group 1, n=29); two or three (group 2, n=21) vascular pools. 26 patients without coronary heart disease and AS were included in the control group. All patients in groups 1 and 2 and 65% of those in the control group took statins. The concentrations of Lp(a), CRP, lipids and blood count were determined., Results: The patients of the three groups did not differ in age. In the groups with AS (79% in group 1 and 85% in group 2), there were more men (relative to 54% in the control group). Diabetes mellitus was more common only in patients with multifocal AS. The absolute number of blood monocytes and leukocytes, the neutrophil-lymphocyte ratio, as well as Lp(a) level were higher in patients of groups 1 and 2 relative to the control. The maximum Lp(a) level (median [25%; 75%]) was observed in patients with lesions of two or more vascular pools vs the control group (49 [4; 96] mg/dL, vs 10 [4; 21] mg/dL, p=0.02). The CRP level was significant elevated in patients from group 2 7.2 [4.0; 9.7] mg/L, relative to group 1 2.5 [1.0; 4.7] mg/L, and the control group 2.9 [1.2; 4.9] mg/L, p0.05. The Lp(a) and CRP concentration, or the presence of diabetes mellitus in patients, regardless of other risk factors, were associated with severe stenosing AS in young and middle age., Conclusion: An elevated concentration of Lp(a) (30 mg/dL) determines the presence of both isolated and multifocal stenosing AS in the examined patients. A simultaneous increase in the concentration of both Lp(a) and CRP, as well as the presence of diabetes mellitus, are associated with the premature development of stenosing atherosclerotic lesions in several vascular regions at once. Measurement of these predictors in young and middle-aged patients makes it possible to use them as biochemical markers to assess the likelihood of multifocal lesions of the vascular pool.
- Published
- 2022
- Full Text
- View/download PDF
176. Author Correction: Clinically applicable artificial intelligence system for dental diagnosis with CBCT.
- Author
-
Ezhov M, Gusarev M, Golitsyna M, Yates JM, Kushnerev E, Tamimi D, Aksoy S, Shumilov E, Sanders A, and Orhan K
- Published
- 2021
- Full Text
- View/download PDF
177. Evaluation of artificial intelligence for detecting impacted third molars on cone-beam computed tomography scans.
- Author
-
Orhan K, Bilgir E, Bayrakdar IS, Ezhov M, Gusarev M, and Shumilov E
- Subjects
- Artificial Intelligence, Cone-Beam Computed Tomography, Humans, Retrospective Studies, Molar, Third diagnostic imaging, Tooth, Impacted diagnostic imaging
- Abstract
Purpose: The aim of this study was to evaluate the diagnostic performance of artificial intelligence (AI) application evaluating of the impacted third molar teeth in Cone-beam Computed Tomography (CBCT) images., Material and Methods: In total, 130 third molar teeth (65 patients) were included in this retrospective study. Impaction detection, Impacted tooth numbers, root/canal numbers of teeth, relationship with adjacent anatomical structures (inferior alveolar canal and maxillary sinus) were compared between the human observer and AI application. Recorded parameters agreement between the human observer and AI application based on the deep-CNN system was evaluated using the Kappa analysis., Results: In total, 112 teeth (86.2%) were detected as impacted by AI. The number of roots was correctly determined in 99 teeth (78.6%) and the number of canals in 82 teeth (68.1%). There was a good agreement in the determination of the inferior alveolar canal in relation to the mandibular impacted third molars (kappa: 0.762) as well as the number of roots detection (kappa: 0.620). Similarly, there was an excellent agreement in relation to maxillary impacted third molar and the maxillary sinus (kappa: 0.860). For the maxillary molar canal number detection, a moderate agreement was found between the human observer and AI examinations (kappa: 0.424)., Conclusions: Artificial Intelligence (AI) application showed high accuracy values in the detection of impacted third molar teeth and their relationship to anatomical structures., (Copyright © 2020 Elsevier Masson SAS. All rights reserved.)
- Published
- 2021
- Full Text
- View/download PDF
178. Clinically applicable artificial intelligence system for dental diagnosis with CBCT.
- Author
-
Ezhov M, Gusarev M, Golitsyna M, Yates JM, Kushnerev E, Tamimi D, Aksoy S, Shumilov E, Sanders A, and Orhan K
- Subjects
- Disease Management, Humans, Image Processing, Computer-Assisted, Observer Variation, Sensitivity and Specificity, Artificial Intelligence, Cone-Beam Computed Tomography methods, Cone-Beam Computed Tomography standards, Stomatognathic Diseases diagnosis
- Abstract
In this study, a novel AI system based on deep learning methods was evaluated to determine its real-time performance of CBCT imaging diagnosis of anatomical landmarks, pathologies, clinical effectiveness, and safety when used by dentists in a clinical setting. The system consists of 5 modules: ROI-localization-module (segmentation of teeth and jaws), tooth-localization and numeration-module, periodontitis-module, caries-localization-module, and periapical-lesion-localization-module. These modules use CNN based on state-of-the-art architectures. In total, 1346 CBCT scans were used to train the modules. After annotation and model development, the AI system was tested for diagnostic capabilities of the Diagnocat AI system. 24 dentists participated in the clinical evaluation of the system. 30 CBCT scans were examined by two groups of dentists, where one group was aided by Diagnocat and the other was unaided. The results for the overall sensitivity and specificity for aided and unaided groups were calculated as an aggregate of all conditions. The sensitivity values for aided and unaided groups were 0.8537 and 0.7672 while specificity was 0.9672 and 0.9616 respectively. There was a statistically significant difference between the groups (p = 0.032). This study showed that the proposed AI system significantly improved the diagnostic capabilities of dentists., (© 2021. The Author(s).)
- Published
- 2021
- Full Text
- View/download PDF
179. A deep learning approach for dental implant planning in cone-beam computed tomography images.
- Author
-
Kurt Bayrakdar S, Orhan K, Bayrakdar IS, Bilgir E, Ezhov M, Gusarev M, and Shumilov E
- Subjects
- Bone Density, Dental Implantation, Humans, Jaw, Edentulous, Partially diagnostic imaging, Mandibular Canal diagnostic imaging, Nasal Cavity diagnostic imaging, Neural Networks, Computer, Patient Care Planning, Radiography, Dental methods, Alveolar Process diagnostic imaging, Cone-Beam Computed Tomography methods, Deep Learning, Dental Implants, Mandible diagnostic imaging, Maxilla diagnostic imaging
- Abstract
Background: The aim of this study was to evaluate the success of the artificial intelligence (AI) system in implant planning using three-dimensional cone-beam computed tomography (CBCT) images., Methods: Seventy-five CBCT images were included in this study. In these images, bone height and thickness in 508 regions where implants were required were measured by a human observer with manual assessment method using InvivoDental 6.0 (Anatomage Inc. San Jose, CA, USA). Also, canals/sinuses/fossae associated with alveolar bones and missing tooth regions were detected. Following, all evaluations were repeated using the deep convolutional neural network (Diagnocat, Inc., San Francisco, USA) The jaws were separated as mandible/maxilla and each jaw was grouped as anterior/premolar/molar teeth region. The data obtained from manual assessment and AI methods were compared using Bland-Altman analysis and Wilcoxon signed rank test., Results: In the bone height measurements, there were no statistically significant differences between AI and manual measurements in the premolar region of mandible and the premolar and molar regions of the maxilla (p > 0.05). In the bone thickness measurements, there were statistically significant differences between AI and manual measurements in all regions of maxilla and mandible (p < 0.001). Also, the percentage of right detection was 72.2% for canals, 66.4% for sinuses/fossae and 95.3% for missing tooth regions., Conclusions: Development of AI systems and their using in future for implant planning will both facilitate the work of physicians and will be a support mechanism in implantology practice to physicians.
- Published
- 2021
- Full Text
- View/download PDF
180. Carotid Intima-Media Thickness Progression as Surrogate Marker for Cardiovascular Risk: Meta-Analysis of 119 Clinical Trials Involving 100 667 Patients.
- Author
-
Willeit P, Tschiderer L, Allara E, Reuber K, Seekircher L, Gao L, Liao X, Lonn E, Gerstein HC, Yusuf S, Brouwers FP, Asselbergs FW, van Gilst W, Anderssen SA, Grobbee DE, Kastelein JJP, Visseren FLJ, Ntaios G, Hatzitolios AI, Savopoulos C, Nieuwkerk PT, Stroes E, Walters M, Higgins P, Dawson J, Gresele P, Guglielmini G, Migliacci R, Ezhov M, Safarova M, Balakhonova T, Sato E, Amaha M, Nakamura T, Kapellas K, Jamieson LM, Skilton M, Blumenthal JA, Hinderliter A, Sherwood A, Smith PJ, van Agtmael MA, Reiss P, van Vonderen MGA, Kiechl S, Klingenschmid G, Sitzer M, Stehouwer CDA, Uthoff H, Zou ZY, Cunha AR, Neves MF, Witham MD, Park HW, Lee MS, Bae JH, Bernal E, Wachtell K, Kjeldsen SE, Olsen MH, Preiss D, Sattar N, Beishuizen E, Huisman MV, Espeland MA, Schmidt C, Agewall S, Ok E, Aşçi G, de Groot E, Grooteman MPC, Blankestijn PJ, Bots ML, Sweeting MJ, Thompson SG, and Lorenz MW
- Subjects
- Female, Humans, Male, Middle Aged, Randomized Controlled Trials as Topic, Carotid Artery, Common diagnostic imaging, Carotid Intima-Media Thickness, Heart Disease Risk Factors, Myocardial Infarction diagnostic imaging, Stroke diagnostic imaging
- Abstract
Background: To quantify the association between effects of interventions on carotid intima-media thickness (cIMT) progression and their effects on cardiovascular disease (CVD) risk., Methods: We systematically collated data from randomized, controlled trials. cIMT was assessed as the mean value at the common-carotid-artery; if unavailable, the maximum value at the common-carotid-artery or other cIMT measures were used. The primary outcome was a combined CVD end point defined as myocardial infarction, stroke, revascularization procedures, or fatal CVD. We estimated intervention effects on cIMT progression and incident CVD for each trial, before relating the 2 using a Bayesian meta-regression approach., Results: We analyzed data of 119 randomized, controlled trials involving 100 667 patients (mean age 62 years, 42% female). Over an average follow-up of 3.7 years, 12 038 patients developed the combined CVD end point. Across all interventions, each 10 μm/y reduction of cIMT progression resulted in a relative risk for CVD of 0.91 (95% Credible Interval, 0.87-0.94), with an additional relative risk for CVD of 0.92 (0.87-0.97) being achieved independent of cIMT progression. Taken together, we estimated that interventions reducing cIMT progression by 10, 20, 30, or 40 μm/y would yield relative risks of 0.84 (0.75-0.93), 0.76 (0.67-0.85), 0.69 (0.59-0.79), or 0.63 (0.52-0.74), respectively. Results were similar when grouping trials by type of intervention, time of conduct, time to ultrasound follow-up, availability of individual-participant data, primary versus secondary prevention trials, type of cIMT measurement, and proportion of female patients., Conclusions: The extent of intervention effects on cIMT progression predicted the degree of CVD risk reduction. This provides a missing link supporting the usefulness of cIMT progression as a surrogate marker for CVD risk in clinical trials.
- Published
- 2020
- Full Text
- View/download PDF
181. Lipoprotein(a) Lowering-From Lipoprotein Apheresis to Antisense Oligonucleotide Approach.
- Author
-
Greco MF, Sirtori CR, Corsini A, Ezhov M, Sampietro T, and Ruscica M
- Abstract
It is well-known that elevated lipoprotein(a)-Lp(a)-levels are associated with a higher risk of cardiovascular (CV) mortality and all-cause mortality, although a standard pharmacotherapeutic approach is still undefined for patients with high CV risk dependent on hyperlipoproteinemia(a). Combined with high Lp(a) levels, familial hypercholesterolemia (FH) leads to a greater CVD risk. In suspected FH patients, the proportion of cases explained by a rise of Lp(a) levels ranges between 5% and 20%. In the absence of a specific pharmacological approach able to lower Lp(a) to the extent required to achieve CV benefits, the most effective strategy today is lipoprotein apheresis (LA). Although limited, a clear effect on Lp(a) is exerted by PCSK9 antagonists, with apparently different mechanisms when given with statins (raised catabolism) or as monotherapy (reduced production). In the era of RNA-based therapies, a new dawn is represented by the use of antisense oligonucleotides APO(a)L
rx , able to reduce Lp(a) from 35% to over 80%, with generally modest injection site reactions. The improved knowledge of Lp(a) atherogenicity and possible prevention will be of benefit for patients with residual CV risk remaining after the most effective available lipid-lowering agents.- Published
- 2020
- Full Text
- View/download PDF
182. [Optimization of lipid-lowering therapy in patients after ischemic stroke. Resolution of the Council of Experts].
- Author
-
Vozniuk IA, Shamalov NA, Ezhov MV, Tikhomirova OV, Gurevich VS, Kucherenko SS, Konovalov GA, Konstantinov VO, and Ershova AI
- Subjects
- Anticholesteremic Agents, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Proprotein Convertase 9, Brain Ischemia drug therapy, Stroke drug therapy
- Abstract
Hyperlipidemia is the main risk factor for diseases caused by atherosclerosis including ischemic stroke. This publication provides practical recommendations and an algorithm for prescribing lipid-lowering therapy to post-ischemic stroke patients. The algorithm presents the steps for sequential administration of statins, ezetimibe, and PCSK9 inhibitors to achieve target levels of low-density lipoprotein cholesterol.
- Published
- 2020
- Full Text
- View/download PDF
183. The Prospective Studies of Atherosclerosis (Proof-ATHERO) Consortium: Design and Rationale.
- Author
-
Tschiderer L, Seekircher L, Klingenschmid G, Izzo R, Baldassarre D, Iglseder B, Calabresi L, Liu J, Price JF, Bae JH, Brouwers FP, de Groot E, Schmidt C, Bergström G, Aşçi G, Gresele P, Okazaki S, Kapellas K, Landecho MF, Sattar N, Agewall S, Zou ZY, Byrne CD, Nanayakkara PWB, Papagianni A, Witham MD, Bernal E, Ekart R, van Agtmael MA, Neves MF, Sato E, Ezhov M, Walters M, Olsen MH, Stolić R, Zozulińska-Ziółkiewicz DA, Hanefeld M, Staub D, Nagai M, Nieuwkerk PT, Huisman MV, Kato A, Honda H, Parraga G, Magliano D, Gabriel R, Rundek T, Espeland MA, Kiechl S, Willeit J, Lind L, Empana JP, Lonn E, Tuomainen TP, Catapano A, Chien KL, Sander D, Kavousi M, Beulens JWJ, Bots ML, Sweeting MJ, Lorenz MW, and Willeit P
- Subjects
- Aged, Cardiovascular Diseases epidemiology, Carotid Intima-Media Thickness, Female, Humans, Male, Middle Aged, Predictive Value of Tests, Prospective Studies, Pulse Wave Analysis, Research Design, Risk Assessment, Risk Factors, Atherosclerosis diagnosis
- Abstract
Atherosclerosis - the pathophysiological mechanism shared by most cardiovascular diseases - can be directly or indirectly assessed by a variety of clinical tests including measurement of carotid intima-media thickness, carotid plaque, -ankle-brachial index, pulse wave velocity, and coronary -artery calcium. The Prospective Studies of Atherosclerosis -(Proof-ATHERO) consortium (https://clinicalepi.i-med.ac.at/research/proof-athero/) collates de-identified individual-participant data of studies with information on atherosclerosis measures, risk factors for cardiovascular disease, and incidence of cardiovascular diseases. It currently comprises 74 studies that involve 106,846 participants from 25 countries and over 40 cities. In summary, 21 studies recruited participants from the general population (n = 67,784), 16 from high-risk populations (n = 22,677), and 37 as part of clinical trials (n = 16,385). Baseline years of contributing studies range from April 1980 to July 2014; the latest follow-up was until June 2019. Mean age at baseline was 59 years (standard deviation: 10) and 50% were female. Over a total of 830,619 person-years of follow-up, 17,270 incident cardiovascular events (including coronary heart disease and stroke) and 13,270 deaths were recorded, corresponding to cumulative incidences of 2.1% and 1.6% per annum, respectively. The consortium is coordinated by the Clinical Epidemiology Team at the Medical University of Innsbruck, Austria. Contributing studies undergo a detailed data cleaning and harmonisation procedure before being incorporated in the Proof-ATHERO central database. Statistical analyses are being conducted according to pre-defined analysis plans and use established methods for individual-participant data meta-analysis. Capitalising on its large sample size, the multi-institutional collaborative Proof-ATHERO consortium aims to better characterise, understand, and predict the development of atherosclerosis and its clinical consequences., (© 2020 S. Karger AG, Basel.)
- Published
- 2020
- Full Text
- View/download PDF
184. The role of red yeast rice (RYR) supplementation in plasma cholesterol control: A review and expert opinion.
- Author
-
Banach M, Bruckert E, Descamps OS, Ellegård L, Ezhov M, Föger B, Fras Z, Kovanen PT, Latkovskis G, März W, Panagiotakos DB, Paragh G, Pella D, Pirillo A, Poli A, Reiner Ž, Silbernagel G, Viigimaa M, Vrablík M, and Catapano AL
- Subjects
- Biological Products adverse effects, Biological Products pharmacokinetics, Biotransformation, Cardiovascular Diseases chemically induced, Cholesterol blood, Clinical Trials as Topic, Cytochrome P-450 CYP3A metabolism, Double-Blind Method, Expert Testimony, Food-Drug Interactions, Gastrointestinal Diseases chemically induced, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors adverse effects, Lovastatin adverse effects, Lovastatin chemistry, Lovastatin pharmacokinetics, Lovastatin therapeutic use, Medicine, Chinese Traditional, Molecular Structure, Multicenter Studies as Topic, Musculoskeletal Diseases chemically induced, Prodrugs pharmacokinetics, Prodrugs therapeutic use, Randomized Controlled Trials as Topic, Self Medication, Biological Products therapeutic use, Dietary Supplements, Hydroxymethylglutaryl-CoA Reductase Inhibitors therapeutic use, Hypercholesterolemia therapy
- Published
- 2019
- Full Text
- View/download PDF
185. Matrix Metalloproteinase 9 as a Predictor of Coronary Atherosclerotic Plaque Instability in Stable Coronary Heart Disease Patients with Elevated Lipoprotein(a) Levels.
- Author
-
Ezhov M, Safarova M, Afanasieva O, Mitroshkin M, Matchin Y, and Pokrovsky S
- Subjects
- Adult, Aged, Biomarkers blood, Biomarkers metabolism, Coronary Disease blood, Coronary Disease metabolism, Female, Humans, Lipoprotein(a) metabolism, Male, Matrix Metalloproteinase 9 metabolism, Middle Aged, Plaque, Atherosclerotic blood, Plaque, Atherosclerotic metabolism, Software, Coronary Angiography, Coronary Disease enzymology, Lipoprotein(a) blood, Matrix Metalloproteinase 9 blood, Plaque, Atherosclerotic enzymology
- Abstract
We sought to investigate whether levels of matrix metalloproteinases (MMPs) and their inhibitors predict coronary atherosclerotic plaque instability, as assessed by intravascular ultrasound (IVUS) virtual histology during coronary angiography. Blood samples were collected before angiography in 32 subjects (mean age 56 ± 8 years) with stable coronary heart disease (CHD) and elevated lipoprotein(a) (Lp(a), 94 ± 35 mg/dL). Levels of high-sensitivity C-reactive protein (hsCRP), apolipoprotein B100 (apoB100), MMP-7, MMP-9, tissue inhibitor of metalloproteinases (TIMP)-1, and TIMP-2 were determined using commercially available enzyme-linked immunosorbent assay kits. Results. The morphology of a total of sixty coronary lesions was assessed by virtual histology IVUS imaging. Eleven (18%) plaques in nine (28%) patients were classified as plaques with an unstable phenotype or a thin-cap fibroatheroma. Age, low-density lipoprotein cholesterol, apoB100, MMP-7, and MMP-9 levels were positively associated with necrotic core volume. Conversely, there was a negative relationship between MMP-7 and -9 levels and fibrous and fibro-fatty tissue volume. Multivariate regression analysis revealed that MMP-9 is a strong independent predictor of atherosclerotic plaque instability in stable CHD patients. In stable CHD patients with elevated Lp(a), MMP-9 levels are positively associated with the size of the necrotic core of coronary atherosclerotic plaques., Competing Interests: The authors declare no conflict of interest.
- Published
- 2019
- Full Text
- View/download PDF
186. Overview of the current status of familial hypercholesterolaemia care in over 60 countries - The EAS Familial Hypercholesterolaemia Studies Collaboration (FHSC).
- Author
-
Vallejo-Vaz AJ, De Marco M, Stevens CAT, Akram A, Freiberger T, Hovingh GK, Kastelein JJP, Mata P, Raal FJ, Santos RD, Soran H, Watts GF, Abifadel M, Aguilar-Salinas CA, Al-Khnifsawi M, AlKindi FA, Alnouri F, Alonso R, Al-Rasadi K, Al-Sarraf A, Ashavaid TF, Binder CJ, Bogsrud MP, Bourbon M, Bruckert E, Chlebus K, Corral P, Descamps O, Durst R, Ezhov M, Fras Z, Genest J, Groselj U, Harada-Shiba M, Kayikcioglu M, Lalic K, Lam CSP, Latkovskis G, Laufs U, Liberopoulos E, Lin J, Maher V, Majano N, Marais AD, März W, Mirrakhimov E, Miserez AR, Mitchenko O, Nawawi HM, Nordestgaard BG, Paragh G, Petrulioniene Z, Pojskic B, Postadzhiyan A, Reda A, Reiner Ž, Sadoh WE, Sahebkar A, Shehab A, Shek AB, Stoll M, Su TC, Subramaniam T, Susekov AV, Symeonides P, Tilney M, Tomlinson B, Truong TH, Tselepis AD, Tybjærg-Hansen A, Vázquez-Cárdenas A, Viigimaa M, Vohnout B, Widén E, Yamashita S, Banach M, Gaita D, Jiang L, Nilsson L, Santos LE, Schunkert H, Tokgözoğlu L, Car J, Catapano AL, and Ray KK
- Subjects
- Anticholesteremic Agents adverse effects, Biomarkers blood, Cholesterol, LDL blood, Cooperative Behavior, Genetic Predisposition to Disease, Health Care Surveys, Health Services Accessibility, Healthcare Disparities, Humans, Hyperlipoproteinemia Type II blood, Hyperlipoproteinemia Type II diagnosis, Hyperlipoproteinemia Type II epidemiology, Phenotype, Predictive Value of Tests, Prevalence, Risk Factors, Treatment Outcome, Anticholesteremic Agents therapeutic use, Blood Component Removal adverse effects, Global Health, Hyperlipoproteinemia Type II therapy, International Cooperation
- Abstract
Background and Aims: Management of familial hypercholesterolaemia (FH) may vary across different settings due to factors related to population characteristics, practice, resources and/or policies. We conducted a survey among the worldwide network of EAS FHSC Lead Investigators to provide an overview of FH status in different countries., Methods: Lead Investigators from countries formally involved in the EAS FHSC by mid-May 2018 were invited to provide a brief report on FH status in their countries, including available information, programmes, initiatives, and management., Results: 63 countries provided reports. Data on FH prevalence are lacking in most countries. Where available, data tend to align with recent estimates, suggesting a higher frequency than that traditionally considered. Low rates of FH detection are reported across all regions. National registries and education programmes to improve FH awareness/knowledge are a recognised priority, but funding is often lacking. In most countries, diagnosis primarily relies on the Dutch Lipid Clinics Network criteria. Although available in many countries, genetic testing is not widely implemented (frequent cost issues). There are only a few national official government programmes for FH. Under-treatment is an issue. FH therapy is not universally reimbursed. PCSK9-inhibitors are available in ∼2/3 countries. Lipoprotein-apheresis is offered in ∼60% countries, although access is limited., Conclusions: FH is a recognised public health concern. Management varies widely across countries, with overall suboptimal identification and under-treatment. Efforts and initiatives to improve FH knowledge and management are underway, including development of national registries, but support, particularly from health authorities, and better funding are greatly needed., (Copyright © 2018 Elsevier B.V. All rights reserved.)
- Published
- 2018
- Full Text
- View/download PDF
187. The association of lipoprotein(a) and apolipoprotein(a) phenotypes with peripheral artery disease.
- Author
-
Tmoyan NA, Ezhov MV, Afanasieva OI, Klesareva EA, Razova OA, Kukharchuk VV, and Pokrovsky SN
- Subjects
- Aged, Atherosclerosis metabolism, Correlation of Data, Female, Humans, Immunoblotting methods, Immunochemistry methods, Male, Middle Aged, Phenotype, Risk Assessment, Risk Factors, Apoprotein(a) analysis, Apoprotein(a) blood, Coronary Disease blood, Coronary Disease epidemiology, Peripheral Arterial Disease blood, Peripheral Arterial Disease epidemiology
- Abstract
Aim: Lipoprotein(a) [Lp(a)] is an independent risk factor of coronary heart disease (CHD) and myocardial infarction. Data about the role of Lp(a) in the development of peripheral artery disease (PAD) is controversial and uncertain. The aim of the study was to evaluate the association between Lp(a), apolipoprotein(a) [apo(a)] phenotypes and PAD., Materials and Methods: The study included 998 patients (707 male and 291 female, average age 60±12). The patients were divided into 4 groups depending on the presence or absence PAD and CHD: group I (n=188, PAD+CHD+), group II (n=78, PAD+CHD-), group III (n=407, PAD-CHD+), group IV (n=325, PAD-CHD-)., Results: The level of Lp(a) was significantly higher in groups I, II, III in comparison with patients of control group (group IV): 34 [15; 80], 30 [10; 49], 22 [8; 60] mg/dl vs. 15 [6; 35] mg/dl respectively, p<0.01 in all cases. Lp(a) level was higher in the group I than in the other groups (p<0.05). The prevalence of elevated Lp(a) level (≥ 30 mg/dl) was significantly higher in groups I, II, III than in control group: 54%, 50%, 43% respectively vs. 30%, p<0.01 in all cases. The prevalence of Lp(a) ≥ 30 mg/dl was more frequent in the group with PAD and CHD than in the group with CHD and without PAD (p=0.02). The odds ratio (OR) of PAD in the presence of elevated Lp(a) level was 1.9 (95%CI, 1.4-2.5, p<0.01). Low molecular weight (LMW) apo(a) phenotype was met more frequently in groups I, II, III compared to group IV: 46%, 56%, 52% respectively vs. 28%, p<0.01. LMW apo(a) in the patients without CHD was associated with PAD (OR 3.3; 95% CI, 1.6-6.8, p<0.01), and there was no association with the patients with CHD. In logistic regression analysis adjusted for age, sex, hypertension, obesity, smoking, diabetes, LDL-C, Lp(a) and LMW apo(a) phenotype were independent predictors of PAD when included separately., Conclusion: Elevated level of Lp(a) and LMW apo(a) phenotype are independent risk factors of PAD. The level of Lp(a) in the patients with PAD and CHD was higher than in the case of isolated lesion of each vascular pool. Higher level of Lp(a) is associated with more severe atherosclerosis involving more than one vascular pools.
- Published
- 2018
- Full Text
- View/download PDF
188. The Role of Nutraceuticals in Statin Intolerant Patients.
- Author
-
Banach M, Patti AM, Giglio RV, Cicero AFG, Atanasov AG, Bajraktari G, Bruckert E, Descamps O, Djuric DM, Ezhov M, Fras Z, von Haehling S, Katsiki N, Langlois M, Latkovskis G, Mancini GBJ, Mikhailidis DP, Mitchenko O, Moriarty PM, Muntner P, Nikolic D, Panagiotakos DB, Paragh G, Paulweber B, Pella D, Pitsavos C, Reiner Ž, Rosano GMC, Rosenson RS, Rysz J, Sahebkar A, Serban MC, Vinereanu D, Vrablík M, Watts GF, Wong ND, and Rizzo M
- Subjects
- Clinical Studies as Topic, Dyslipidemias diet therapy, Humans, Dietary Supplements, Dyslipidemias drug therapy, Hydroxymethylglutaryl-CoA Reductase Inhibitors adverse effects
- Abstract
Statins are the most common drugs administered for patients with cardiovascular disease. However, due to statin-associated muscle symptoms, adherence to statin therapy is challenging in clinical practice. Certain nutraceuticals, such as red yeast rice, bergamot, berberine, artichoke, soluble fiber, and plant sterols and stanols alone or in combination with each other, as well as with ezetimibe, might be considered as an alternative or add-on therapy to statins, although there is still insufficient evidence available with respect to long-term safety and effectiveness on cardiovascular disease prevention and treatment. These nutraceuticals could exert significant lipid-lowering activity and might present multiple non-lipid-lowering actions, including improvement of endothelial dysfunction and arterial stiffness, as well as anti-inflammatory and antioxidative properties. The aim of this expert opinion paper is to provide the first attempt at recommendation on the management of statin intolerance through the use of nutraceuticals with particular attention on those with effective low-density lipoprotein cholesterol reduction., (Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)
- Published
- 2018
- Full Text
- View/download PDF
189. [The Role of Lipoprotein(a) in the Development of Peripheral and Carotid Atherosclerosis].
- Author
-
Tmoyan NA, Afanasieva OI, and Ezhov MV
- Subjects
- Apolipoprotein B-100 metabolism, Atherosclerosis metabolism, Cardiovascular Diseases, Carotid Artery Diseases metabolism, Humans, Risk Factors, Atherosclerosis etiology, Carotid Artery Diseases etiology, Lipoprotein(a) metabolism
- Abstract
Lipoprotein(a) [Lp(a)] consists of an LDL-like particle in which the apolipoprotein B100 is covalently bound to apolipoprotein(a) by a single disulfide bond. Lp(a) is synthesized in the liver and its plasma concentration varies from 0 to 400 mg/dl. Increased level of Lp(a) is considered to be an independent risk factor of cardiovascular diseases and coronary heart disease. Data about the significance of hyperlipoproteinemia(a) in the development of atherosclerosis of peripheral (lower limbs) and carotid arteries remain controversial. This review is devoted to Lp(a), its relationship with atherosclerosis of different vascular beds, as well as modern possibilities of hyperlipoproteinemia(a) correction.
- Published
- 2018
190. Specific Lp(a) apheresis: A tool to prove lipoprotein(a) atherogenicity.
- Author
-
Pokrovsky SN, Afanasieva OI, Safarova MS, Balakhonova TV, Matchin YG, Adamova IYU, Konovalov GA, and Ezhov MV
- Subjects
- Atorvastatin therapeutic use, Biomarkers blood, Carotid Artery Diseases blood, Carotid Artery Diseases diagnostic imaging, Carotid Intima-Media Thickness, Cholesterol, LDL blood, Coronary Angiography, Coronary Artery Disease blood, Coronary Artery Disease diagnostic imaging, Coronary Stenosis blood, Coronary Stenosis diagnostic imaging, Dyslipidemias blood, Dyslipidemias diagnosis, Female, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors therapeutic use, Inflammation Mediators blood, Male, Middle Aged, Plaque, Atherosclerotic, Prospective Studies, Risk Factors, Time Factors, Treatment Outcome, Ultrasonography, Interventional, Blood Component Removal methods, Carotid Artery Diseases therapy, Coronary Artery Disease therapy, Coronary Stenosis therapy, Dyslipidemias therapy, Lipoprotein(a) blood
- Abstract
Background: An elevated lipoprotein(a) (Lp(a)) level is observed in more than 30% of patients with stable ischemic heart disease (SIHD). We conducted an investigation of the effects of specific Lp(a) apheresis on the progression of atherosclerosis in SIHD patients with Lp(a) levels greater than 50 mg/dL., Methods: We prospectively enrolled 15 patients diagnosed with SIHD based on symptom-driven coronary angiography findings, with Lp(a) ≥50 mg/dL and a low density lipoprotein cholesterol (LDL-C) ≤2.5 mmol/L, who were on long-term statin therapy. They underwent weekly Lp(a) apheresis using Lp(a) Lipopak
® adsorption columns which contain monospecific sheep polyclonal antibodies against human Lp(a). Fifteen age and gender matched SIHD patients receiving atorvastatin monotherapy served as controls. At baseline and 18 months post-treatment, quantitative coronary angiography, intracoronary ultrasound with virtual histology and carotid ultrasound were performed. Lipid profile, including Lp(a), was measured at the scheduled visits, and before and after each apheresis procedure. Levels of high-sensitivity C-reactive protein (hsCRP), matrix metalloproteinases (MMP)-7 and 9, and tissue inhibitor of matrix metalloproteinases (TIMP)-1 and 2 were determined at baseline and at the end of the study period., Results: Each specific Lp(a) apheresis procedure was carried out with two adsorption columns resulting in an average acute decrease in Lp(a) levels of 75% (from 110 ± 22 to 29 ± 16 mg/dL) without significant changes in other plasma components. Lp(a) reduction over the course of 18 months was associated with a decrease in the mean percent diameter stenosis of 5.05% and an increase in minimal lumen diameter of 14%; the mean total atheroma volume was reduced by 4.60 mm3 (p < 0.05 for all). There was a decrease in absolute common carotid intima-media thickness in the Lp(a) apheresis group of 0.07 ± 0.15 mm both from baseline and compared with the control group (p = 0.01). Levels of hsCRP were reduced by 40% in patients on Lp(a) apheresis without significant changes in the levels of other biomarkers at the end of the study., Conclusion: Reduction of the atherosclerotic burden in coronary and carotid arteries was observed in patients treated with specific Lp(a) apheresis and statin over 18 months compared with statin therapy alone. These findings support the atherogenic role of Lp(a) and reinforce the need to assess the effects of Lp(a)-lowering on cardiovascular events and mortality. Trial Registration Clinicaltrials.gov (NCT02133807)., (Copyright © 2017 Elsevier B.V. All rights reserved.)- Published
- 2017
- Full Text
- View/download PDF
191. Lipid-lowering nutraceuticals in clinical practice: position paper from an International Lipid Expert Panel.
- Author
-
Cicero AFG, Colletti A, Bajraktari G, Descamps O, Djuric DM, Ezhov M, Fras Z, Katsiki N, Langlois M, Latkovskis G, Panagiotakos DB, Paragh G, Mikhailidis DP, Mitchenko O, Paulweber B, Pella D, Pitsavos C, Reiner Ž, Ray KK, Rizzo M, Sahebkar A, Serban MC, Sperling LS, Toth PP, Vinereanu D, Vrablík M, Wong ND, and Banach M
- Subjects
- Cardiovascular Diseases blood, Cardiovascular Diseases drug therapy, Cholesterol, HDL blood, Cholesterol, LDL blood, Drug Interactions, Dyslipidemias blood, Dyslipidemias drug therapy, Evidence-Based Medicine, Fatty Acids, Unsaturated administration & dosage, Fatty Acids, Unsaturated blood, Fatty Acids, Unsaturated pharmacokinetics, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors therapeutic use, Intestinal Absorption drug effects, Life Style, Liver drug effects, Liver metabolism, Meta-Analysis as Topic, Observational Studies as Topic, Phytochemicals administration & dosage, Phytochemicals blood, Phytochemicals pharmacokinetics, Probiotics administration & dosage, Probiotics pharmacokinetics, Randomized Controlled Trials as Topic, Risk Factors, Triglycerides blood, Cardiovascular Diseases epidemiology, Dietary Supplements, Dyslipidemias epidemiology
- Abstract
In recent years, there has been growing interest in the possible use of nutraceuticals to improve and optimize dyslipidemia control and therapy. Based on the data from available studies, nutraceuticals might help patients obtain theraputic lipid goals and reduce cardiovascular residual risk. Some nutraceuticals have essential lipid-lowering properties confirmed in studies; some might also have possible positive effects on nonlipid cardiovascular risk factors and have been shown to improve early markers of vascular health such as endothelial function and pulse wave velocity. However, the clinical evidence supporting the use of a single lipid-lowering nutraceutical or a combination of them is largely variable and, for many of the nutraceuticals, the evidence is very limited and, therefore, often debatable. The purpose of this position paper is to provide consensus-based recommendations for the optimal use of lipid-lowering nutraceuticals to manage dyslipidemia in patients who are still not on statin therapy, patients who are on statin or combination therapy but have not achieved lipid goals, and patients with statin intolerance. This statement is intended for physicians and other healthcare professionals engaged in the diagnosis and management of patients with lipid disorders, especially in the primary care setting., (© The Author(s) 2017. Published by Oxford University Press on behalf of the International Life Sciences Institute. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)
- Published
- 2017
- Full Text
- View/download PDF
192. Automatic identification of variables in epidemiological datasets using logic regression.
- Author
-
Lorenz MW, Abdi NA, Scheckenbach F, Pflug A, Bülbül A, Catapano AL, Agewall S, Ezhov M, Bots ML, Kiechl S, and Orth A
- Subjects
- Algorithms, Carotid Intima-Media Thickness, Data Mining, Humans, Meta-Analysis as Topic, Predictive Value of Tests, Prognosis, Carotid Artery Diseases diagnostic imaging, Databases, Factual, Epidemiologic Factors, Logistic Models, Medical Informatics Applications
- Abstract
Background: For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable., Methods: For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated., Results: In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables., Conclusions: We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies.
- Published
- 2017
- Full Text
- View/download PDF
193. Normative values for carotid intima media thickness and its progression: Are they transferrable outside of their cohort of origin?
- Author
-
Liao X, Norata GD, Polak JF, Stehouwer CD, Catapano A, Rundek T, Ezhov M, Sander D, Thompson SG, Lorenz MW, Balakhonova T, Safarova M, Grigore L, Empana JP, Lin HJ, McLachlan S, Bokemark L, Ronkainen K, Schminke U, Lind L, Willeit P, Yanez DN, Steinmetz H, Poppert H, Desvarieux M, Ikram MA, Johnsen SH, Iglseder B, Friera A, Xie W, Plichart M, Su TC, Srinivasan SR, Schmidt C, Tuomainen TP, Völzke H, Nijpels G, Willeit J, Franco OH, Suarez C, Zhao D, Ducimetiere P, Chien KL, Robertson C, Bergström G, Kauhanen J, Dörr M, Dekker JM, Kiechl S, Sitzer M, Bickel H, Sacco RL, Hofman A, Mathiesen EB, Gabriel R, Liu J, Berenson G, Kavousi M, and Price JF
- Subjects
- Atherosclerosis diagnosis, Disease Progression, Global Health, Humans, Incidence, Reference Values, Risk Factors, Atherosclerosis epidemiology, Carotid Intima-Media Thickness
- Abstract
Background: The clinical use of carotid intima media thickness (cIMT) requires normal values, which may be subject to variation of geographical factors, ethnicity or measurement details. The influence of these factors has rarely been studied. The aim of this study was to determine whether normative cIMT values and their association with event risk are generalizable across populations., Design: Meta-analysis of individual participant data., Method: From 22 general population cohorts from Europe, North America and Asia we selected subjects free of cardiovascular disease. Percentiles of cIMT and cIMT progression were assessed separately for every cohort. Cox proportional hazards models for vascular events were used to estimate hazard ratios for cIMT in each cohort. The estimates were pooled across Europe, North America and Asia, with random effects meta-analysis. The influence of geography, ethnicity and ultrasound protocols on cIMT values and on the hazard ratios was examined by meta-regression., Results: Geographical factors, ethnicity and the ultrasound protocol had influence neither on the percentiles of cIMT and its progression, nor on the hazard ratios of cIMT for vascular events. Heterogeneity for percentiles of cIMT and cIMT progression was too large to create meaningful normative values., Conclusions: The distribution of cIMT values is too heterogeneous to define universal or regional population reference values. CIMT values vary widely between different studies regardless of ethnicity, geographic location and ultrasound protocol. Prediction of vascular events with cIMT values was more consistent across all cohorts, ethnicities and regions., (© The European Society of Cardiology 2016.)
- Published
- 2016
- Full Text
- View/download PDF
194. [Elevated Lipoprotein(a) Cncentration and Presence of Subfractions of Small Dense Low Density Lipoproteins as Independent Factors of Risk of Ischemic Heart Disease].
- Author
-
Afanasieva OI, Utkina EA, Artemieva NV, Ezhov MV, Adamova IY, and Pokrovsky SN
- Subjects
- Aged, Apolipoprotein B-100 blood, Coronary Artery Disease blood, Female, Humans, Male, Middle Aged, Risk Factors, Coronary Artery Disease etiology, Lipoprotein(a) blood, Lipoproteins, LDL blood
- Abstract
Aim: To study relation of lipoproteina - Lp(a) and subfractional composition of apoB containing lipoproteins to the presence of ischemic heart disease (IHD). Manerial and methods. Parameters of lipid spectrum, Lp(a), and subfractions of apoB containing lipoproteins were determined in blood serum of 187 patients with known data of instrumental examination., Results: Lp(a) concentration was not linked to any of risk factors, levels total cholesterol (TC), low and high density lipoprotein CH, and subfractions of lipoproteins. In total group triglyceride (TGG) level correlated with content of small dense LDL (sdLDL) (r=0.445, <0.0001) and mean dimension of LDL particles (r=-0.424, p<0.0001). This correlation was absent in the subgroup with Lp(a) more or equal 30 mg/dl and was strengthered among patients with normal Lp(a) level. In total group presence of IHD was associated with sex (r=0.325, p<0.0001), Lp(a) concentration (r=0.271, p=0.0001), and level of triglycerides (r=0.159, p=0.030). In multiple regression analysis levels of TG, Lp(a) and sdLDL were selected as factors independently associated with presence of IHD. Detection of subfractions sdLDL>2 mg/dl in blood plasma (atherogenic profile B), as well as lowering of concentration of large LDL subfractions significantly increased probability of IHD presence in patients with elevated Lp(a) concentration Lp(a) concentration., Conclusion: Lp(a) is an independent factor of risk of coronary atherosclerosis more significant than shifts in subfractional composition of apoB containing lipoproteins. In patients with Lp(a) concentration less or equal 30 mg/dl subfractions of sdLDL were directly related to TG. Level of sdLDL and large lipoproteins of intermediate density are directly related to the presence of IHD. Large LDL correlates with concentration of HDL DL C and probably is cardioprotective. sdLDL content>2 mg/l or hypertriglyceridemia (TG>1.7 mmol/l) significantly increase chances of detection of confirmed IHD in patients with elevated Lp(a).
- Published
- 2016
- Full Text
- View/download PDF
195. [Degenerative Aortic Stenosis: Modern View on Development, Course, and Management].
- Author
-
Burdeinaya AL, Safarova MS, Ezhov MV, and Kukharchuk VV
- Subjects
- Calcinosis, Heart Defects, Congenital, Humans, Hypertrophy, Left Ventricular, Aortic Valve Stenosis epidemiology, Aortic Valve Stenosis etiology, Aortic Valve Stenosis physiopathology, Aortic Valve Stenosis therapy
- Abstract
Degenerative aortic stenosis is an acquired heart defect manifesting as progressive thickening and calcification of leaflets of originally normal tricuspid or congenital bicuspid aortic valve with development of orifice narrowing, left ventricular hypertrophy, and high risk of cardiovascular complications. In this review we present modern concepts of formation and progression of degenerative aortic stenosis and discuss optimal methods of management of this disease.
- Published
- 2016
- Full Text
- View/download PDF
196. Specific Lipoprotein(a) apheresis attenuates progression of carotid intima-media thickness in coronary heart disease patients with high lipoprotein(a) levels.
- Author
-
Ezhov MV, Safarova MS, Afanasieva OI, Pogorelova OA, Tripoten MI, Adamova IY, Konovalov GA, Balakhonova TV, and Pokrovsky SN
- Subjects
- Adult, Atorvastatin therapeutic use, Biomarkers blood, Carotid Artery Diseases diagnostic imaging, Carotid Artery Diseases etiology, Cholesterol, LDL blood, Coronary Angiography, Coronary Disease diagnosis, Disease Progression, Female, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors therapeutic use, Hyperlipoproteinemias blood, Hyperlipoproteinemias complications, Hyperlipoproteinemias diagnosis, Male, Middle Aged, Prospective Studies, Russia, Time Factors, Treatment Outcome, Up-Regulation, Blood Component Removal methods, Carotid Artery Diseases prevention & control, Carotid Artery, Common diagnostic imaging, Carotid Intima-Media Thickness, Coronary Disease complications, Hyperlipoproteinemias therapy, Immunosorbent Techniques, Lipoprotein(a) blood, Ultrasonography, Doppler, Duplex
- Abstract
Background: To date, there have been no studies evaluating the effect of isolated lipoprotein(a) (Lp(a)) lowering therapy on carotid atherosclerosis progression., Methods: We enrolled 30 patients who had coronary heart disease (CHD) verified by angiography, Lp(a) level ≥50 mg/dL, and low density lipoprotein cholesterol (LDL-C) level ≤2.6 mmol/L (100 mg/dL) on chronic statin therapy. Subjects were allocated in a 1:1 ratio to receive apheresis treatment on a weekly basis with immunoadsorption columns ("Lp(a) Lipopak"(®), POCARD Ltd., Russia) added to atorvastatin, or atorvastatin monotherapy. The primary efficacy end-point was the change from baseline in the mean intima-media thickness (IMT) of the common carotid arteries., Results: After one month run-in period with stable atorvastatin dose, LDL-C level was 2.3 ± 0.3 mmol/L and Lp(a) - 105 ± 37 mg/dL. As a result of acute effect of specific Lp(a) apheresis procedures, Lp(a) level decreased by an average of 73 ± 12% to a mean of 29 ± 16 mg/dL, and mean LDL-C decreased by 17 ± 3% to a mean of 1.8 ± 0.2 mmol/L. In the apheresis group, changes in carotid IMT at 9 and 18 months from baseline were -0.03 ± 0.09 mm (p = 0.05) and -0.07 ± 0.15 mm (p = 0.01), respectively. In the atorvastatin group no significant changes in lipid and lipoprotein parameters as well as in carotid IMT were received over 18-month period. Two years after study termination carotid IMT increased by an average of 0.02 ± 0.08 mm in apheresis group and by 0.06 ± 0.10 mm in the control group (p = 0.033)., Conclusion: Isolated extracorporeal Lp(a) elimination over an 18 months period produced regression of carotid intima-media thickness in stable CHD patients with high Lp(a) levels. This effect was maintained for two years after the end of study., Trial Registration: Clinicaltrials.gov (NCT02133807)., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)
- Published
- 2015
- Full Text
- View/download PDF
197. Lowering of lipoprotein(a) level under niacin treatment is dependent on apolipoprotein(a) phenotype.
- Author
-
Artemeva NV, Safarova MS, Ezhov MV, Afanasieva OI, Dmitrieva OA, and Pokrovsky SN
- Subjects
- Adult, Biomarkers blood, Down-Regulation, Humans, Hyperlipoproteinemias blood, Hyperlipoproteinemias diagnosis, Male, Middle Aged, Molecular Weight, Patient Selection, Phenotype, Predictive Value of Tests, Prospective Studies, Russia, Time Factors, Treatment Outcome, Apoprotein(a) blood, Hyperlipoproteinemias drug therapy, Hypolipidemic Agents therapeutic use, Lipoprotein(a) blood, Niacin therapeutic use
- Abstract
Background: Lipoprotein(a) [Lp(a)] is a cardiovascular risk factor; in addition to being a low-density lipoprotein (LDL)-like particle, it contains highly heterogeneous apolipoprotein(a) [apo(a)]. No prior studies have evaluated extended-release (ER) niacin effect on Lp(a) level depending on apo(a) phenotype., Methods: For this 24-week, prospective, open-label clinical trial we recruited 30 men (mean age 46.2 ± 7.5 years) with Lp(a) levels >20 mg/dL. No participant had previously received lipid lowering therapy, and started ER niacin 500 mg with stepwise dose increasing up to 1.5-2.0 g. Subjects were evaluated for Lp(a), lipids, high-sensitivity C-reactive protein, lipoprotein-associated phospholipase A2 (Lp-PLA2), and fibrinolytic markers (plasminogen activator inhibitor-1, tissue plasminogen activator/plasminogen activator inhibitor-1 complex, plasmin-antiplasmin complex). Patients were divided into two groups with major low- (LMW) or high-molecular weight (HMW) apo(a) isoforms determined by sodium dodecyl sulfate-polyacrylamide gel electrophoresis of plasma under reducing conditions followed by immunoblotting., Results: At baseline, groups were comparable in age, lipid, inflammatory and fibrinolytic biomarkers levels. There was a significant difference in baseline Lp(a) concentrations: 92 ± 29 mg/dL versus 54 ± 46 mg/dL in LMW and HMW apo(a) groups, respectively, p < 0.01. During the course of niacin treatment Lp(a) decreased by 28% (p < 0.003), Lp-PLA2 by 22% (p < 0.001), C-reactive protein by 24% (p = 0.07) in LMW apo(a) group, whereas no changes in Lp(a) and biomarkers levels were obtained in HMW apo(a) group., Conclusion: High-dose ER niacin declines elevated Lp(a) level in male subjects with low- but not high-molecular weight apo(a) phenotype., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)
- Published
- 2015
- Full Text
- View/download PDF
198. [Evolution of Lipoprotein(a): From Biomarker to the Therapeutic Target].
- Author
-
Safarova MS and Ezhov MV
- Abstract
Series of experimental, epidemiological, and genetic studies have demonstrated that elevated lipoprotein(a) [Lp(a)] level is associated with cardiovascular disease independently from traditional risk factors of atherosclerosis. This review covers the basics of Lp(a) pathogenicity in atherothrombosis and scrutinizes the biology of proinflammatory activity of the particle. We describe the evidence base around Lp(a) as an independent cardiovascular risk factor by giving an update on the results of epidemiological studies and genetic findings. We have summarized present evidence of Lp(a) lowering strategies and their impact on clinical outcomes in patients with high Lp(a) levels. We highlight a rationale for increased investigational efforts to further assess whether targeting Lp(a) levels minimizes cardiovascular risk.
- Published
- 2015
199. [The Evolution of Views on Lipoprotein(a): From Biomarker to the Therapeutic Target].
- Author
-
Safarova MS and Ezhov MV
- Subjects
- Biomarkers metabolism, Humans, Risk Factors, Cardiovascular Diseases blood, Cardiovascular Diseases drug therapy, Cardiovascular Diseases epidemiology, Hypolipidemic Agents pharmacology, Lipoprotein(a) metabolism
- Abstract
Series of experimental, epidemiological, and genetic studies have demonstrated that elevated lipoprotein(a) [Lp(a)] level is associated with cardiovascular disease independently from traditional risk factors of atherosclerosis. This review covers the basics of Lp(a) pathogenicity in atherothrombosis and scrutinizes the biology of proinflammatory activity of the particle. We describe the evidence base around Lp(a) as an independent cardiovascular risk factor by giving an update on the results of epidemiological studies and genetic findings. We have summarized present evidence of Lp(a) lowering strategies and their impact on clinical outcomes in patients with high Lp(a) levels. We highlight a rationale for increased investigational efforts to further assess whether targeting Lp(a) levels minimizes cardiovascular risk.
- Published
- 2015
200. [Transcatheter Treatment of Degenerative Critical Aortic Valve Stenosis in a Patient With Severe Heart Failure and Chronic Lymphocytic Leukemia].
- Author
-
Safarova MS, Imaev TE, Lorie YY, Saidova MA, and Ezhov MV
- Abstract
Surgical aortic valve replacement is the standard therapy for severe aortic valve stenosis, however one third of patients are rejected because of high surgical risk. Under medical treatment alone these patients have a very poor prognosis with a high mortality rate. We present a case of 70-year-old male patient with degenerative symptomatic critical aortic stenosis and chronic lymphocytic leukemia. Due to recurrence.
- Published
- 2015
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.