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1. A Machine Learning Approach to Screen for Otitis Media Using Digital Otoscope Images Labelled by an Expert Panel

Author

Josefin Sandström, Hermanus Myburgh, Claude Laurent, De Wet Swanepoel, and Thorbjörn Lundberg

Subjects
artificial intelligence, machine learning, convolutional neural network, otitis media, global health, digital imaging, Medicine (General), R5-920
Abstract

Background: Otitis media includes several common inflammatory conditions of the middle ear that can have severe complications if left untreated. Correctly identifying otitis media can be difficult and a screening system supported by machine learning would be valuable for this prevalent disease. This study investigated the performance of a convolutional neural network in screening for otitis media using digital otoscopic images labelled by an expert panel. Methods: Five experienced otologists diagnosed 347 tympanic membrane images captured with a digital otoscope. Images with a majority expert diagnosis (n = 273) were categorized into three screening groups Normal, Pathological and Wax, and the same images were used for training and testing of the convolutional neural network. Expert panel diagnoses were compared to the convolutional neural network classification. Different approaches to the convolutional neural network were tested to identify the best performing model. Results: Overall accuracy of the convolutional neural network was above 0.9 in all except one approach. Sensitivity to finding ears with wax or pathology was above 93% in all cases and specificity was 100%. Adding more images to train the convolutional neural network had no positive impact on the results. Modifications such as normalization of datasets and image augmentation enhanced the performance in some instances. Conclusions: A machine learning approach could be used on digital otoscopic images to accurately screen for otitis media.

Published
2022
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2. Otitis Media Diagnosis for Developing Countries Using Tympanic Membrane Image-Analysis

Author

Hermanus C. Myburgh, Willemien H. van Zijl, DeWet Swanepoel, Sten Hellström, and Claude Laurent

Subjects
Decision tree, Feature extraction, Automated diagnosis, Otitis media, Video-otoscope, Global medicine, Medicine, Medicine (General), R5-920
Abstract

Background: Otitis media is one of the most common childhood diseases worldwide, but because of lack of doctors and health personnel in developing countries it is often misdiagnosed or not diagnosed at all. This may lead to serious, and life-threatening complications. There is, thus a need for an automated computer based image-analyzing system that could assist in making accurate otitis media diagnoses anywhere. Methods: A method for automated diagnosis of otitis media is proposed. The method uses image-processing techniques to classify otitis media. The system is trained using high quality pre-assessed images of tympanic membranes, captured by digital video-otoscopes, and classifies undiagnosed images into five otitis media categories based on predefined signs. Several verification tests analyzed the classification capability of the method. Findings: An accuracy of 80.6% was achieved for images taken with commercial video-otoscopes, while an accuracy of 78.7% was achieved for images captured on-site with a low cost custom-made video-otoscope. Interpretation: The high accuracy of the proposed otitis media classification system compares well with the classification accuracy of general practitioners and pediatricians (~64% to 80%) using traditional otoscopes, and therefore holds promise for the future in making automated diagnosis of otitis media in medically underserved populations.

Published
2016
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3. COMPARISON OF DİSCRETE WAVELET TRANSFORM AND COMPLEX WAVELET TRANSFORM IN HYBRID SKELETONIZATION BASED ON CVANN

Author

Murat CEYLAN, Osman Nuri UCAN, Yüksel ÖZBAY, Rachid JENNANE, Gabriel AUFORT, and Claude Laurent BENHAMOU

Subjects
Wavelet transform, complex wavelet transform, complex-valued artificial neural network, General Works
Abstract

Curve and surface thinning are widely-used skeletonization techniques for modeling objects in 3 dimensions. In the case of disordered porous media analysis, however, neither is really efficient since the internal geometry of the object is usually composed of both rod and plate shapes. This paper concludes an application of discrete wavelet transform (WT) and complex wavelet transform (CWT) in image processing problem such as hybrid skeletonization of trabecular bone images. Hybrid skeleton combines 2D surfaces and 1D curve to represent respectively the plate-shaped and rod-shaped parts of the object. For hybrid skeletonization, two cascade structures are proposed. In these structures, features of images were extracted with discrete wavelet transform and complex wavelet transform. After that, obtained features were used as inputs of complex-valued artificial neural network (CVANN) which is multi-layered artificial neural networks with two dimensions (real and imaginary parts). Effects of the feature extraction methods are compared for ability of the hybrid skeletonization on a trabecular bone sample. Results show that the CWT succeeded to hybrid skeletonization with lower error rate than WT.

Published
2013

4. Odanacatib for the treatment of postmenopausal osteoporosis: results of the LOFT multicentre, randomised, double-blind, placebo-controlled trial and LOFT Extension study

Author

Mautalén, Carlos Alfredo, Man, Zulema, Zanchetta, Jose Ruben, Magaril, Clelia Haydee, Sambrook, Philip, Reginster, Jean-Yves, Geusens, Piet, Goemaere, Stefan, Albergaria, Ben Hur, Zerbini, Cristiano Augusto de Freitas, Castro, Marise Lazaretti, Gregorio, Luiz Henrique, Stoilov, Rumen, Borissova, Anna-Maria I, Hristozov, Kiril Hristov, Temelkova, Nataliya L, Daskalova, Ivona Kirilova, Kuzmanova, Stefka Ivanova, Yaneva-Bichovska, Daniela, Batalov, Anastas Zgurov, Riedemann, Pablo, Rodriguez Portales, José Adolfo, Tang, Hai, Zhu, hanmin, Zhang, Zhenlin, Chao, Aijun, Hu, Yali, Liu, Zhiming, Lu, Juming, Qiu, Mingcai, Gao, Xin, Zhang, Shaofen, Xu, Ling, Xia, Weibo, Liao, Eryuan, Yang, Wenying, Wu, Wen, Dai, Kerong, Hu, Renming, Jaller, Juan Jose, Cabal, Francisco, Molina, José Fernando, Cure Cure, Carlos A, Yupanqui-Lozno, Hernan, Chalem, Philippe, Londono, John, Abello, Mauricio, Tobias, Edgardo D, Otero, William, Nikolic, Tatjana, Miskic, Blazenka, Stepan, Jan, Vyskocil, Vaclav, Novosad, Libor, Slesinger, Jan, Novosad, Pavel, Vlckova, Erika, Bortlik, Ladislav, Dokoupilova, Eva, Hala, Tomas, Jensen, Jens-Erik Beck, Brixen, Kim Torsten, Langdahl, Bente Lomholt, Schwarz, Peter, Eskildsen, Peter Claes, Eiken, Pia Agnete, Hermann, Anne Pernille, Gram, Jeppe, Schou, Maiken Brix, Alexandersen, Peter, Nedergaard, Bettina, Mejía, Dolores Magdalena, Estrella De Henriquez, Lourdes, Páez, Norka, Velazco, Casimiro, Valter, Ivo, Vahula, Kadri-Liina, Kull, Ingrid, Maasalu, Katre, Chapurlat, Roland, Fardellone, Patrice, Benhamou, Claude Laurent, Roux, Christian, Weryha, Georges, Herkt, Volkmar, Martz, Rene, Nischik, Ruth, Spieler, Wolfgang, Contzen, Christel, Felsenberg, Dieter, Frieling, Isolde, Frahm, Eike, Briones, Henry, Sandoval, Boris, Barrios, Patricia, García, Abraham, Avendaño, Carlos, González, Magdalena, Guerra, Jeremías, Tuna, Maria, Díaz, Olga Marina, Samayoa, Eduardo, López, Edgar, Barrera, José Raúl, Palencia, Mainor, Cifuentes, Mayra, Alvarado, Georgina, López, Miriam, Chavez, Nilmo, Haase, Franklin, Rivera, Ruddy, González, Claudio, Tan, Kathryn, Leung, Ping Chung, Mandalam, Sheshadri, Pitale, Shailesh Umakant, Bantwal, Ganapathi, Ammini, Ariachery Chinamma, Shaikh, Shehla Sajid Akhta, Kanakatte Mylariah, Prasanna Kumar, Dharmalingam, Mala, Mukhopadhyay, Satinath, Jain, Arpit, Singh, Parminder, Shetty, Naresh, Sathyanarayana, Srikanta Shamanna, Shah, Nalini, Chadha, Manoj Dharam, Bhandankar, Rajendra, Velayutham, Kumaravel, Marwah, Sudha, John, Mathew, Sahay, Rakesh Kumar, Adami, Silvano, Nuti, Ranuccio, Bianchi, Gerolamo, Brandi, Maria Luisa, Minisola, Salvatore, Fiore, Carmelo Erio, Rubinacci, Alessandro, Miyajima, Hisayuki, Yamane, Hiroo, Nakatani, Yuji, Okamoto, Sumiaki, Kuroda, Koji, Fujimori, Motoaki, Itabashi, Akira, Katayama, Kuniaki, Nakajo, Satoru, Somekawa, Yoshiaki, Ohsawa, Yoshimitsu, Tajima, Wataru, Mizuno, Katsunori, Mori, Shigeru, Kanabuchi, Takato, Hashizume, Hiroyuki, Oka, Nobuyuki, Hamada, Kazutoshi, Yamaguchi, Motoi, Hirahara, Fumiki, Atobe, Masaaki, Ohtake, Yoshiharu, Ichikawa, Shuichi, Onishi, Tomoyuki, Matsumoto, Kou, Nakamura, Tetsuro, Shirasawa, Eishi, Katayama, Ko, Takahashi, Mitsugu, Oguma, Tadanori, Matsui, Hideo, Katoh, Yoshiharu, Shigenobu, Keiichi, Onishi, Tsutomu, Shibukawa, Masato, Ikeda, Satoshi, Osaka, Kazuhiro, Kanda, Ryosuke, Inobe, Yoshito, Shigenobu, Masaharu, Hasegawa, Morimasa, Yamaji, Tetsuo, Miyazaki, Yu, Ito, Takayasu, Nakamura, Eisuke, Nagai, Shinji, Lim, Sung-Kil, Chung, Yoon-Sok, Shin, Chan-Soo, Min, Yong-Ki, Kim, Ghi Su, Yoon, Hyun Koo, Kang, Moo-Il, Yang, Kyu-Hyun, Park, Hyoung Moo, Kim, In Joo, Chung, Dong Jin, Chung, Ho Yeon, Jaundzeikare, Sandra, Andersone, Dace, Medne, Agita, Yaghi, Yasser, Alekna, Vidmantas, Kasiulevicius, Vytautas, Purtokaite - Labutiniene, Irina, Krasauskiene, Aurelija, Varanaviciene, Jurate, Basijokiene, Vida, Abraitiene, Agne, Radzeviciene, Lina, Walliser, Jesus, García Hernández, Pedro Alberto, Araujo, Maria Frida, Avila Armengol, Hilario Ernesto, De la Peña, Pilar, Tamayo, Juan, Zazueta, Beatriz, Cons, Fidencio, Gilchrist, Nigel Leslie, Reid, Ian Reginald, Leikis, Robert, Jones, Peter, Singh, Joe Gragrath Pradeep, Halse, Johan Inge, Syversen, Unni, Høivik, Hans Olav, Øfjord, Erik Snorre, Gulseth, Hans Christian, Elle, Sigbjørn, Norheim, Paal Dag, Calvo Quiroz, Armando A., Cesar Augusto, Pastor A., León Portocarrero, Manuel Gustavo, Vidal Neira, Luis Fernando, Chavez, Jose, Garro Barrera, Boris, Kuroiwa Sampei, Rita, Luis Fernando, Bellatín V., Oquelis Cabredo, Rogger, Castillo, Sonia, Morales, Agustin Miguel G, Tan, Perry Pua, Leagogo, Liberato Antonio C, Jr., Wang, Edward HM, Li-Yu, Julie T, Sawicki, Andrzej Z, Stasiuk, Barbara, Kania, Grzegorz, Lorenc, Roman, Sidorowicz-Bialynicka, Anna, Szczepanski, Leszek, Franek, Edward, Filip, Rafal, Sekula, Jan, Blicharski, Tomasz, Leszczynski, Piotr, Sewerynek, Ewa, Miazgowski, Tomasz, Milewicz, Andrzej, Dabrowska, Magda, Romaszko, Jerzy, Pluskiewicz, Wojciech, Wojnowski, Lukasz, Codreanu, Catalin, Bolosiu, Horatiu, Ionescu, Ruxandra, Zosin, Ioana, Macovei, Liviu, Bojinca, Mihai, Radulescu, Florin, Pop, Simona, Sarbu, Adrian, Benevolenskaya, Lidia I, Nasonov, Evgeny L, Rozhinskaya, Lyudmila Ya, Oganov, Raphael G, Rodionova, Svetlana S, Shlyakhto, Eugeny Vladimirovich, Trofimov, Vasiliy, Zotkin, Eugeny G, Zazerskaya, Irina E, Grineva, Elena N, Ershova, Olga, Lesnyak, Olga, Ostroumova, Olga D, Malichenko, Svetlana B, Pikhlak, Eduard G, Pilyaev, Valery G, Raskina, Tatiana, Zonova, Elena V, Shirinsky, Valery S, Dimic, Aleksandar N, Cobeljic, Goran, Vujovic, Svetlana, Ellis, Graham Charlston, Lipschitz, Stanley, De Villiers, Tobias Johannes, De Weerd, Albert Jan, Vally, Tasneem, Trinder, Yvonne, Coetsee, Jacobus Ludewikus, Davis, Charles Pierre, Nayiager, Savithree, Hough, Frans Stephanus, Oelofse, Louis F, van der Walt, Eugene, Lombaard, Johannes Jurgens, Blignaut, Suzanne, Govind, Uttam, Fouche, Leon Frederik, Kruger, Dawid Stephanus, Dalmeyer, Johannes Paul, Ferreira, Mada M, Escudero-Contreras, Alejandro, Muñoz Torres, Manuel, Hawkins Carranza, Federico, Perez Castrillon, Jose Luis, García Meijide, Juan Antonio, Jodar Gimeno, Esteban, Palacios Gil-Antuñana, Santiago, de Teresa Parreno, Luis, Martín Mola, Emilio, Alvarez Sanchez, Carmen, Lippuner, Kurt, Tsai, Keh-Sung, Tu, Shih-Te, Chen, Jung-Fu, Lee, Oscar Kuang-Sheng, Hsu, Wen-Wei, Grygorieva, Natalia Viktorivna, Povoroznyuk, Vladyslav Volodymyrovych, Korzh, Mykola Oleksiiovych, Loskutov, Oleksandr Levgeniiovych, Chukov, Andriy Borysovych, Sarmiento, Rex, Thomas, Hawys, Donnachie, Hugh, Pavel-Knox, Irina, Shaw, Hilary, Hassanin, Hana, Abdulhakim, Essam Eldin Ahmed, Savani, Naren, Bachmann, Gloria A, Barrett-Connor, Elizabeth, Binkley, Neil C, Bone, Henry G, Brandon, Donald M, Checketts, Darin David, Fraser, Neil J, Watts, Nelson B, Geller, Steven A, Gimbel, Joseph S, Greenwald, Maria White, Holt, Peter A, Johnston, Cyrus Conrad, Fang, Chien, Kiel, Douglas P, Klashman, David J, Lewiecki, E. Michael, Lowenstein, Mitchell B, McClung, Michael Roy, Nattrass, Susan M, Odio, Alberto, Levengood, Julie, Romaguera, Josefina, Saag, Kenneth G, Sebai, Mohamed Bassam, Snyder, Brian, Kutner, Mark Eliot, Streja, Dan, Schwartz, Elliott P, Christiansen, Mark G, McClung, Michael R, O'Donoghue, Michelle L, Papapoulos, Socrates E, Bone, Henry, Langdahl, Bente, Reid, Ian R, Cavallari, Ilaria, Bonaca, Marc P, Wiviott, Stephen D, de Villiers, Tobias, Ling, Xu, Nakamura, Toshitaka, Rodriguez-Portales, Jose Adolfo, Zanchetta, José, Zerbini, Cristiano A F, Park, Jeong-Gun, Im, KyungAh, Cange, Abby, Grip, Laura T, Heyden, Norman, DaSilva, Carolyn, Cohn, Dosinda, Massaad, Rachid, Scott, Boyd B, Verbruggen, Nadia, Gurner, Deborah, Miller, Deborah L, Blair, Micki L, Polis, Adam B, Stoch, S Aubrey, Santora, Arthur, Lombardi, Antonio, Leung, Albert T, Kaufman, Keith D, and Sabatine, Marc S

Published
2019
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6. Score de l’os trabéculaire : le point

Author

Bousson, Valérie, Bergot, Catherine, Sutter, Bruno, Thomas, Thierry, Bendavid, Sauveur, Benhamou, Claude-Laurent, Blain, Hubert, Brazier, Michel, Breuil, Véronique, Briot, Karine, Chapurlat, Roland, Chapuis, Laure, Cohen Solal, Martine, Fardellone, Patrice, Feron, Jean-Marc, Gauvain, Jean-Bernard, Laroche, Michel, Legrand, Erick, Lespessailles, Eric, Linglart, Agnès, Marcelli, Christian, Roux, Christian, Souberbielle, Jean-Claude, Tremollieres, Florence, Weryha, Georges, and Cortet, Bernard

Published
2016
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7. Trabecular Bone Score: Where are we now?

Author

Bousson, Valérie, Bergot, Catherine, Sutter, Bruno, Thomas, Thierry, Bendavid, Sauveur, Benhamou, Claude-Laurent, Blain, Hubert, Brazier, Michel, Breuil, Véronique, Briot, Karine, Chapurlat, Roland, Chapuis, Laure, Cohen Solal, Martine, Fardellone, Patrice, Feron, Jean-Marc, Gauvain, Jean-Bernard, Laroche, Michel, Legrand, Erick, Lespessailles, Eric, Linglart, Agnès, Marcelli, Christian, Roux, Christian, Souberbielle, Jean-Claude, Tremollieres, Florence, Weryha, Georges, and Cortet, Bernard

Published
2015
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8. Usefulness of bone density measurement in fallers

Author

Blain, Hubert, Rolland, Yves, Beauchet, Olivier, Annweiler, Cedric, Benhamou, Claude-Laurent, Benetos, Athanase, Berrut, Gilles, Audran, Maurice, Bendavid, Sauveur, Bousson, Valérie, Briot, Karine, Brazier, Michel, Breuil, Véronique, Chapuis, Laure, Chapurlat, Roland, Cohen-Solal, Martine, Cortet, Bernard, Dargent, Patricia, Fardellone, Patrice, Feron, Jean-Marc, Gauvain, Jean-Bernard, Guggenbuhl, Pascal, Hanon, Olivier, Laroche, Michel, Kolta, Sami, Lespessailles, Éric, Letombe, Brigitte, Mallet, Éric, Marcelli, Christian, Orcel, Philippe, Puisieux, François, Seret, Patrick, Souberbielle, Jean-Claude, Sutter, Bruno, Trémollières, Florence, Weryha, Georges, Roux, Christian, and Thomas, Thierry

Published
2014
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9. Intérêt de l’ostéodensitométrie chez les sujets chuteurs

Author

Blain, Hubert, Rolland, Yves, Beauchet, Olivier, Annweiler, Cedric, Benhamou, Claude-Laurent, Benetos, Athanase, Berrut, Gilles, Audran, Maurice, Bendavid, Sauveur, Bousson, Valérie, Briot, Karine, Brazier, Michel, Breuil, Véronique, Chapuis, Laure, Chapurlat, Roland, Cohen-Solal, Martine, Cortet, Bernard, Dargent, Patricia, Fardellone, Patrice, Feron, Jean-Marc, Gauvain, Jean-Bernard, Guggenbuhl, Pascal, Hanon, Olivier, Laroche, Michel, Kolta, Sami, Lespessailles, Eric, Letombe, Brigitte, Mallet, Eric, Marcelli, Christian, Orcel, Philippe, Puisieux, François, Seret, Patrick, Souberbielle, Jean-Claude, Sutter, Bruno, Trémollières, Florence, Weryha, Georges, Roux, Christian, and Thomas, Thierry

Published
2014
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17. Texture Image Analysis for Osteoporosis Detection with Morphological Tools

Author

Sevestre-Ghalila, Sylvie, Benazza-Benyahia, Amel, Ricordeau, Anne, Mellouli, Nedra, Chappard, Christine, Benhamou, Claude Laurent, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Barillot, Christian, editor, Haynor, David R., editor, and Hellier, Pierre, editor

Published
2004
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23. Congestive Heart Failure

Author

Torosoff, Mikhail, Sader, Claude-Laurent, Philbin, Edward F., III, Cannon, Christopher P., editor, and Weintraub, William S., editor

Published
2003
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33. Accuracy and Reliability of Smartphone Self-Test Audiometry in Community Clinics in Low Income Settings: A Comparative Study

Author

Thorbjörn Lundberg, De Wet Swanepoel, Göran Umefjord, Josefin Sandstrom, and Claude Laurent

Subjects
Adult, Male, Telemedicine, 020205 medical informatics, Hearing loss, 02 engineering and technology, Sensitivity and Specificity, Diagnostic Self Evaluation, South Africa, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Audiometry, Health care, 0202 electrical engineering, electronic engineering, information engineering, Global health, Humans, Medicine, Mobile technology, Hearing Loss, 030223 otorhinolaryngology, mHealth, Reliability (statistics), Aged, Aged, 80 and over, medicine.diagnostic_test, business.industry, Reproducibility of Results, General Medicine, Middle Aged, medicine.disease, Mobile Applications, Otorhinolaryngology, Audiometry, Pure-Tone, Female, Smartphone, Medical emergency, medicine.symptom, business
Abstract

Background: There is a lack of hearing health care globally, and tele-audiology and mobile technologies have been proposed as important strategies to reduce the shortfall. Objectives: To investigate the accuracy and reliability of smartphone self-test audiometry in adults, in community clinics in low-income settings. Methods: A prospective, intra-individual, repeated measurements design was used. Sixty-three adult participants (mean age 52 years, range 20-88 years) were recruited from ENT and primary health care clinics in a low-income community in Tshwane, South Africa. Air conduction hearing thresholds for octave frequencies 0.5 to 8 kHz collected with the smartphone self-test in non-sound treated environments were compared to those obtained by reference audiometry. Results: The overall mean difference between threshold seeking methods (ie, smartphone thresholds subtracted from reference) was −2.2 dB HL (n = 467 thresholds, P = 0.00). Agreement was within 10 dB HL for 80.1% (n = 467 thresholds) of all threshold comparisons. Sensitivity for detection hearing loss >40 dB HL in one ear was 90.6% (n = 84 ears), and specificity 94.2% (n = 84 ears). Conclusion: Smartphone self-test audiometry can provide accurate and reliable air conduction hearing thresholds for adults in community clinics in low-income settings.

Published
2020
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42. ZOLEDRONOVAYa KISLOTA V PROFILAKTIKE POTERI KOSTNOY TKANI U zhENShchIN POSTMENOPAUZAL'NOGO VOZRASTA S OSTEOPENIEY

Author

Michael Mcclung, Paul Miller, Chris Recknor, Peter Mesenbrink, Christina Bucci-Rechtweg, and Claude-Laurent Benhamou

Subjects
Osteopathy, RZ301-397.5
Abstract

Профилактика остеопоротических переломов, особенно бедренной кости и позвонков, - это важная проблема здравоохранения. Подобные переломы сопровождаются повышенным риском осложнений и смерти, поэтому эффективная стратегия их профилактики может оказать значительное влияние на заболеваемость и несколько меньшее, но существенное влияние на смертность пожилых людей. 1-3 Хотя у женщин с остепенией риск развития переломов ниже, чем у женщин того же возраста с остеопорозом, тем не менее, при отсутствии лечения у них высока вероятность развития остеопороза. Более того, большинство переломов регистрируют у пациенток с остеопенией. 4 В последних рекомендациях женщинам постменопаузального возраста с остеопенией и со средним или высоким риском переломов (оценивают с помощью валидированных методов, таких как FRAX) предлагается назначать лекарственные средства, предназначенные для лечения остеопороза. 5 Пероральные бисфосфонаты предупреждают потерю костной ткани после наступления менопаузы у женщин более молодого и старшего возраста 6-8 Однако в клинической практике многие пациентки плохо выполняют рекомендации врача и принимают пероральные бисфосфонаты в течение не более нескольких месяцев. 9 В связи с этим важное значение имеет применение эффективного препарата, обеспечивающего высокую приверженность пациенток. В клинических исследованиях доказано, что ежегодные инфузии золедроновой кислоты в дозе 5 мг в течение 3 лет снижают риск переломов позвонков, бедренной кости и внепозвоночных переломов и увеличивают МПК поясничных позвонков и бедренной кости у женщин с постменопаузальным остеопорозом. 10 Кроме того, препарат снижал риск повторных клинически явных переломов у мужчин и женщин, недавно перенесших остеопоротический перелом бедренной кости. 11 Целью данного исследования было изучение эффективности и переносимости внутривенных инфузий золедроновой кислоты в дозе 5 мг у женщин постменопаузального возраста с остеопенией. В 2-летнем исследовании изучали эффективность двух и одной инфузии препарата, чтобы оценить возможность сокращения числа инфузий для профилактики потери костной ткани.

Published
2011
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