175 results on '"Ziaeian, B"'
Search Results
2. Cardiovascular Disease: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines (vol 74, e177, 209)
- Author
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Arnett, DK, Blumenthal, RS, Albert, MA, Buroker, AB, Goldberger, ZD, Hahn, EJ, Himmelfarb, CD, Khera, A, Lloyd-Jones, D, McEvoy, JW, Michos, ED, Miedema, MD, Munoz, D, Smith, JR, Virani, SS, Williams, KA, Yeboah, J, and Ziaeian, B
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Cardiovascular System & Hematology ,Cardiorespiratory Medicine and Haematology ,Public Health and Health Services - Published
- 2020
3. Correction
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Arnett, DK, Blumenthal, RS, Albert, MA, Buroker, AB, Goldberger, ZD, Hahn, EJ, Himmelfarb, CD, Khera, A, Lloyd-Jones, D, McEvoy, JW, Michos, ED, Miedema, MD, Munoz, D, Smith, SC Jr, Virani, SS, Williams, KA Jr, Yeboah, J, and Ziaeian, B
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Biomedical and Clinical Sciences ,Cardiovascular Medicine and Haematology ,Cardiorespiratory Medicine and Haematology ,Public Health and Health Services ,Cardiovascular System & Hematology ,Cardiovascular medicine and haematology - Published
- 2019
4. Arterial Thrombosis in Patients with Cancer.
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Tuzovic, M, Herrmann, J, Iliescu, C, Marmagkiolis, K, Ziaeian, B, and Yang, EH
- Abstract
Cancer is a common cause of morbidity and mortality in the USA. While the association between venous thrombosis and malignancy is well established, arterial thrombosis has more recently been recognized as a serious complication of cancer and certain chemotherapeutic agents. This review aims to summarize the most recent literature regarding the incidence and risk factors for cancer-related arterial thrombosis, understand the pathophysiologic mechanisms of thrombosis, and highlight the specific diagnostic and treatment considerations relevant to cancer patients.Based on a recent study looking at the Surveillance, Epidemiology, and End Results (SEER) database, the incidence of arterial thromboembolic events (ATEs) in patients with cancer at 6 months is 4.7%; the presence of an ATE is predictive of worse outcomes. Certain drugs such as platinum-based agents, vascular endothelial growth factor inhibitors, tyrosine kinase inhibitors, and taxanes have been associated with high rates of ATEs. Increased platelet reactivity appears crucial to development of arterial thrombosis in cancer patients. Cancer patients have an increased risk of arterial thrombosis that is likely due to both a cancer-associated procoagulant state as well as the adverse effects of certain chemotherapeutic agents. Treatment of arterial thromboembolism in cancer patients typically requires a multidisciplinary approach in part due to high rates of thrombocytopenia and stent thrombosis in the setting of percutaneous interventions. More studies are needed to investigate optimal prophylaxis, surveillance strategies, and treatments of cancer-related arterial thromboembolic disease.
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- 2018
5. Preventing heart failure hospital readmissions: Challenges and opportunities
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Ziaeian, B and Fonarow, GC
- Abstract
Heart failure (HF) is a leading cause of hospitalization and readmission. As evidence-based treatments for the management of HF with reduced ejection fraction have evolved, the ability to reduce the HF readmission risk has improved. Clinical trials have shown measurable improvements in patient-centered outcomes through exercise, pharmacologic, and device therapies. In contrast, for HF with preserved ejection fraction, no medical therapy has been identified that improves survival, though aldosterone antagonists may reduce HF hospitalization risk. Thirty-day readmission rates have become a metric for hospital quality and financial penalties in the United States; however, reducing all preventable hospitalizations, improving health status, and prolonging survival should be the goal for HF patients. Nearly half of repeat hospitalizations for HF are secondary to noncardiovascular conditions. Careful attention to complicating comorbid conditions should be assessed before discharge for an acute decompensation. Optimizing the outpatient management of HF and providing careful transitions from the hospital to the outpatient setting are critical to minimizing readmission risk and improving patient-centered outcomes.
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- 2017
6. Correction
- Author
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Fonarow, GC and Ziaeian, B
- Subjects
Biomedical and Clinical Sciences ,Cardiovascular Medicine and Haematology ,Cardiorespiratory Medicine and Haematology ,Public Health and Health Services ,Cardiovascular System & Hematology ,Cardiovascular medicine and haematology - Published
- 2016
7. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
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Brauer, M, Roth, G, Aravkin, A, Zheng, P, Abate, K, Abate, Y, Abbafati, C, Abbasgholizadeh, R, Abbasi, M, Abbasian, M, Abbasifard, M, Abbasi-Kangevari, M, Abd ElHafeez, S, Abd-Elsalam, S, Abdi, P, Abdollahi, M, Abdoun, M, Abdulah, D, Abdullahi, A, Abebe, M, Abedi, A, Abegaz, T, Abeldaño Zuñiga, R, Abiodun, O, Abiso, T, Aboagye, R, Abolhassani, H, Abouzid, M, Aboye, G, Abreu, L, Abualruz, H, Abubakar, B, Abu-Gharbieh, E, Abukhadijah, H, Aburuz, S, Abu-Zaid, A, Adane, M, Addo, I, Addolorato, G, Adedoyin, R, Adekanmbi, V, Aden, B, Adetunji, J, Adeyeoluwa, T, Adha, R, Adibi, A, Adnani, Q, Adzigbli, L, Afolabi, A, Afolabi, R, Afshin, A, Afyouni, S, Afzal, M, Afzal, S, Agampodi, S, Agbozo, F, Aghamiri, S, Agodi, A, Agrawal, A, Agyemang-Duah, W, Ahinkorah, B, Ahmad, A, Ahmad, D, Ahmad, F, Ahmad, N, Ahmad, S, Ahmad, T, Ahmed, A, Ahmed, L, Ahmed, M, Ahmed, S, Ajami, M, Akalu, G, Akara, E, Akbarialiabad, H, Akhlaghi, S, Akinosoglou, K, Akinyemiju, T, Akkaif, M, Akkala, S, Akombi-Inyang, B, Al Awaidy, S, Al Hasan, S, Alahdab, F, AL-Ahdal, T, Alalalmeh, S, Alalwan, T, Al-Aly, Z, Alam, K, Alam, N, Alanezi, F, Alanzi, T, Albakri, A, Albataineh, M, Aldhaleei, W, Aldridge, R, Alemayohu, M, Alemu, Y, Al-Fatly, B, Al-Gheethi, A, Al-Habbal, K, Alhabib, K, Alhassan, R, Ali, A, Ali, B, Ali, I, Ali, L, Ali, M, Ali, R, Ali, S, Ali, W, Alicandro, G, Alif, S, Aljunid, S, Alla, F, Al-Marwani, S, Al-Mekhlafi, H, Almustanyir, S, Alomari, M, Alonso, J, Alqahtani, J, Alqutaibi, A, Al-Raddadi, R, Alrawashdeh, A, Al-Rifai, R, Alrousan, S, Al-Sabah, S, Alshahrani, N, Altaany, Z, Altaf, A, Al-Tawfiq, J, Altirkawi, K, Aluh, D, Alvis-Guzman, N, Alvis-Zakzuk, N, Alwafi, H, Al-Wardat, M, Al-Worafi, Y, Aly, H, Aly, S, Alzoubi, K, Al-Zyoud, W, Amaechi, U, Aman Mohammadi, M, Amani, R, Amiri, S, Amirzade-Iranaq, M, Ammirati, E, Amu, H, Amugsi, D, Amusa, G, Ancuceanu, R, Anderlini, D, Anderson, J, Andrade, P, Andrei, C, Andrei, T, Anenberg, S, Angappan, D, Angus, C, Anil, A, Anil, S, Anjum, A, Anoushiravani, A, Antonazzo, I, Antony, C, Antriyandarti, E, Anuoluwa, B, Anvari, D, Anvari, S, Anwar, S, Anwer, R, Anyabolo, E, Anyasodor, A, Apostol, G, Arabloo, J, Arabzadeh Bahri, R, Arafat, M, Areda, D, Aregawi, B, Aremu, A, Armocida, B, Arndt, M, Ärnlöv, J, Arooj, M, Artamonov, A, Artanti, K, Aruleba, I, Arumugam, A, Asbeutah, A, Asgary, S, Asgedom, A, Ashbaugh, C, Ashemo, M, Ashraf, T, Askarinejad, A, Assmus, M, Astell-Burt, T, Athar, M, Athari, S, Atorkey, P, Atreya, A, Aujayeb, A, Ausloos, M, Avila-Burgos, L, Awoke, A, Ayala Quintanilla, B, Ayatollahi, H, Ayestas Portugal, C, Ayuso-Mateos, J, Azadnajafabad, S, Azevedo, R, Azhar, G, Azizi, H, Azzam, A, Backhaus, I, Badar, M, Badiye, A, Bagga, A, Baghdadi, S, Bagheri, N, Bagherieh, S, Bahrami Taghanaki, P, Bai, R, Baig, A, Baker, J, Bakkannavar, S, Balasubramanian, M, Baltatu, O, Bam, K, Bandyopadhyay, S, Banik, B, Banik, P, Banke-Thomas, A, Bansal, H, Barchitta, M, Bardhan, M, Bardideh, E, Barker-Collo, S, Bärnighausen, T, Barone-Adesi, F, Barqawi, H, Barrero, L, Barrow, A, Barteit, S, Basharat, Z, Basiru, A, Basso, J, Bastan, M, Basu, S, Batchu, S, Batra, K, Batra, R, Baune, B, Bayati, M, Bayileyegn, N, Beaney, T, Behnoush, A, Beiranvand, M, Béjot, Y, Bekele, A, Belgaumi, U, Bell, A, Bell, M, Bello, M, Bello, O, Belo, L, Beloukas, A, Bendak, S, Bennett, D, Bennitt, F, Bensenor, I, Benzian, H, Beran, A, Berezvai, Z, Bernabe, E, Bernstein, R, Bettencourt, P, Bhagavathula, A, Bhala, N, Bhandari, D, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bhat, A, Bhat, V, Bhatti, G, Bhatti, J, Bhatti, M, Bhatti, R, Bhuiyan, M, Bhutta, Z, Bikbov, B, Bishai, J, Bisignano, C, Biswas, A, Biswas, B, Biswas, R, Bjørge, T, Boachie, M, Boakye, H, Bockarie, M, Bodolica, V, Bodunrin, A, Bogale, E, Bolla, S, Boloor, A, Bonakdar Hashemi, M, Boppana, S, Bora Basara, B, Borhany, H, Botero Carvajal, A, Bouaoud, S, Boufous, S, Bourne, R, Boxe, C, Braithwaite, D, Brant, L, Brar, A, Breitborde, N, Breitner, S, Brenner, H, Briko, A, Britton, G, Brown, C, Browne, A, Brunoni, A, Bryazka, D, Bulamu, N, Bulto, L, Buonsenso, D, Burkart, K, Burns, R, Busse, R, Bustanji, Y, Butt, N, Butt, Z, Caetano dos Santos, F, Cagney, J, Cahuana-Hurtado, L, Calina, D, Cámera, L, Campos, L, Campos-Nonato, I, Cao, C, Cao, F, Cao, Y, Capodici, A, Cárdenas, R, Carr, S, Carreras, G, Carrero, J, Carugno, A, Carvalho, F, Carvalho, M, Castaldelli-Maia, J, Castañeda-Orjuela, C, Castelpietra, G, Catalá-López, F, Catapano, A, Cattaruzza, M, Caye, A, Cederroth, C, Cegolon, L, Cenderadewi, M, Cercy, K, Cerin, E, Chadwick, J, Chakraborty, C, Chakraborty, P, Chakraborty, S, Chan, J, Chan, R, Chandan, J, Chandika, R, Chaturvedi, P, Chen, A, Chen, C, Chen, H, Chen, M, Chen, S, Cheng, C, Cheng, E, Cherbuin, N, Chi, G, Chichagi, F, Chimed-Ochir, O, Chimoriya, R, Ching, P, Chirinos-Caceres, J, Chitheer, A, Cho, W, Chong, B, Chopra, H, Chowdhury, R, Christopher, D, Chu, D, Chukwu, I, Chung, E, Chung, S, Chutiyami, M, Cioffi, I, Cogen, R, Cohen, A, Columbus, A, Conde, J, Corlateanu, A, Cortese, S, Cortesi, P, Costa, V, Costanzo, S, Criqui, M, Cruz, J, Cruz-Martins, N, Culbreth, G, da Silva, A, Dadras, O, Dai, X, Dai, Z, Daikwo, P, Dalli, L, Damiani, G, D'Amico, E, D'Anna, L, Darwesh, A, Das, J, Das, S, Dash, N, Dashti, M, Dávila-Cervantes, C, Davis Weaver, N, Davitoiu, D, De la Hoz, F, de la Torre-Luque, A, De Leo, D, Debopadhaya, S, Degenhardt, L, Del Bo', C, Delgado-Enciso, I, Delgado-Saborit, J, Demoze, C, Denova-Gutiérrez, E, Dervenis, N, Dervišević, E, Desai, H, Desai, R, Devanbu, V, Dewan, S, Dhali, A, Dhama, K, Dhane, A, Dhimal, M, Dhingra, S, Dhulipala, V, Dhungana, R, Dias da Silva, D, Diaz, D, Diaz, L, Diaz, M, Dima, A, Ding, D, Dinu, M, Djalalinia, S, Do, T, do Prado, C, Dodangeh, M, Dohare, S, Dokova, K, Dong, W, Dongarwar, D, D'Oria, M, Dorostkar, F, Dorsey, E, Doshi, R, Doshmangir, L, Dowou, R, Driscoll, T, Dsouza, A, Dsouza, H, Dumith, S, Duncan, B, Duraes, A, Duraisamy, S, Dushpanova, A, Dzianach, P, Dziedzic, A, Ebrahimi, A, Echieh, C, Ed-Dra, A, Edinur, H, Edvardsson, D, Edvardsson, K, Efendi, F, Eftekharimehrabad, A, Eini, E, Ekholuenetale, M, Ekundayo, T, El Arab, R, El Sayed Zaki, M, El-Dahiyat, F, Elemam, N, Elgar, F, Elgohary, G, Elhabashy, H, Elhadi, M, Elmehrath, A, Elmeligy, O, Elshaer, M, Elsohaby, I, Emeto, T, Esfandiari, N, Eshrati, B, Eslami, M, Esmaeili, S, Estep, K, Etaee, F, Fabin, N, Fagbamigbe, A, Fagbule, O, Fahimi, S, Falzone, L, Fareed, M, Farinha, C, Faris, M, Faris, P, Faro, A, Fasina, F, Fatehizadeh, A, Fauk, N, Fazylov, T, Feigin, V, Feng, X, Fereshtehnejad, S, Feroze, A, Ferrara, P, Ferrari, A, Ferreira, N, Fetensa, G, Feyisa, B, Filip, I, Fischer, F, Fitriana, I, Flavel, J, Flohr, C, Flood, D, Flor, L, Foigt, N, Folayan, M, Force, L, Fortuna, D, Foschi, M, Franklin, R, Freitas, A, Friedman, S, Fux, B, G, S, Gaal, P, Gaihre, S, Gajdács, M, Galali, Y, Gallus, S, Gandhi, A, Ganesan, B, Ganiyani, M, Garcia, V, Gardner, W, Garg, R, Gautam, R, Gebi, T, Gebregergis, M, Gebrehiwot, M, Gebremariam, T, Gebremeskel, T, Gerema, U, Getacher, L, Getahun, G, Getie, M, Ghadirian, F, Ghafarian, S, Ghaffari Jolfayi, A, Ghailan, K, Ghajar, A, Ghasemi, M, Ghasempour Dabaghi, G, Ghasemzadeh, A, Ghassemi, F, Ghazy, R, Gholami, A, Gholamrezanezhad, A, Gholizadeh, N, Ghorbani, M, Gil, A, Gil, G, Gilbertson, N, Gill, P, Gill, T, Gindaba, E, Girmay, A, Glasbey, J, Gnedovskaya, E, Göbölös, L, Godinho, M, Goel, A, Golechha, M, Goleij, P, Golinelli, D, Gomes, N, Gopalani, S, Gorini, G, Goudarzi, H, Goulart, A, Gouravani, M, Goyal, A, Graham, S, Grivna, M, Grosso, G, Guan, S, Guarducci, G, Gubari, M, Guha, A, Guicciardi, S, Gulati, S, Gulisashvili, D, Gunawardane, D, Guo, C, Gupta, A, Gupta, B, Gupta, M, Gupta, R, Gupta, S, Gupta, V, Habibzadeh, F, Habibzadeh, P, Hadaro, T, Hadian, Z, Haep, N, Haghi-Aminjan, H, Haghmorad, D, Hagins, H, Haile, D, Hailu, A, Hajj Ali, A, Halboub, E, Halimi, A, Hall, B, Haller, S, Halwani, R, Hamadeh, R, Hamdy, N, Hameed, S, Hamidi, S, Hammoud, A, Hanif, A, Hanifi, N, Haq, Z, Haque, M, Harapan, H, Hargono, A, Haro, J, Hasaballah, A, Hasan, I, Hasan, M, Hasan, S, Hasani, H, Hasanian, M, Hashmeh, N, Hasnain, M, Hassan, A, Hassan, I, Hassan Zadeh Tabatabaei, M, Hassani, S, Hassanipour, S, Hassankhani, H, Haubold, J, Havmoeller, R, Hay, S, Hebert, J, Hegazi, O, Hegena, T, Heidari, G, Heidari, M, Helfer, B, Hemmati, M, Henson, C, Herbert, M, Herteliu, C, Heuer, A, Hezam, K, Hinneh, T, Hiraike, Y, Hoan, N, Holla, R, Hon, J, Hoque, M, Horita, N, Hossain, S, Hosseini, S, Hosseinzadeh, H, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hoven, H, Hsairi, M, Hsu, J, Hu, C, Huang, J, Huda, M, Hulland, E, Hultström, M, Hushmandi, K, Hussain, J, Hussein, N, Huynh, C, Huynh, H, Ibitoye, S, Idowu, O, Ihler, A, Ikeda, N, Ikuta, K, Ilesanmi, O, Ilic, I, Ilic, M, Imam, M, Immurana, M, Inbaraj, L, Irham, L, Isa, M, Islam, M, Ismail, F, Ismail, N, Iso, H, Isola, G, Iwagami, M, Iwu, C, Iwu-Jaja, C, J, V, Jaafari, J, Jacob, L, Jacobsen, K, Jadidi-Niaragh, F, Jahankhani, K, Jahanmehr, N, Jahrami, H, Jain, A, Jain, N, Jairoun, A, Jaiswal, A, Jakovljevic, M, Jalilzadeh Yengejeh, R, Jamora, R, Jatau, A, Javadov, S, Javaheri, T, Jayaram, S, Jeganathan, J, Jeswani, B, Jiang, H, Johnson, C, Jokar, M, Jomehzadeh, N, Jonas, J, Joo, T, Joseph, A, Joseph, N, Joshi, V, Joshua, C, Jozwiak, J, Jürisson, M, Kaambwa, B, Kabir, A, Kabir, Z, Kadashetti, V, Kahn, E, Kalani, R, Kaliyadan, F, Kalra, S, Kamath, R, Kanagasabai, T, Kanchan, T, Kandel, H, Kanmiki, E, Kanmodi, K, Kansal, S, Kapner, D, Kapoor, N, Karagiannidis, E, Karajizadeh, M, Karakasis, P, Karanth, S, Karaye, I, Karch, A, Karim, A, Karimi, H, Karmakar, S, Kashoo, F, Kasraei, H, Kassahun, W, Kassebaum, N, Kassel, M, Katikireddi, S, Kauppila, J, Kawakami, N, Kaydi, N, Kayode, G, Kazemi, F, Keiyoro, P, Kemmer, L, Kempen, J, Kerr, J, Kesse-Guyot, E, Khader, Y, Khafaie, M, Khajuria, H, Khalaji, A, Khalil, M, Khalilian, A, Khamesipour, F, Khan, A, Khan, M, Khanmohammadi, S, Khatab, K, Khatatbeh, H, Khatatbeh, M, Khatib, M, Khavandegar, A, Khayat Kashani, H, Khidri, F, Khodadoust, E, Khormali, M, Khorrami, Z, Khosla, A, Khosrowjerdi, M, Khreis, H, Khusun, H, Kifle, Z, Kim, K, Kim, M, Kim, Y, Kimokoti, R, Kisa, A, Kisa, S, Knibbs, L, Knudsen, A, Koh, D, Kolahi, A, Kompani, F, Kong, J, Koren, G, Korja, M, Korshunov, V, Korzh, O, Kosen, S, Kothari, N, Koul, P, Koulmane Laxminarayana, S, Krishan, K, Krishnamoorthy, V, Krishnamoorthy, Y, Krishnan, B, Krohn, K, Kuate Defo, B, Kucuk Bicer, B, Kuddus, M, Kugbey, N, Kuitunen, I, Kulimbet, M, Kulkarni, V, Kumar, A, Kumar, N, Kumar, V, Kundu, S, Kurmi, O, Kusnali, A, Kusuma, D, Kutluk, T, La Vecchia, C, Ladan, M, Laflamme, L, Lahariya, C, Lai, D, Lal, D, Lallukka, T, Lám, J, Lan, Q, Lan, T, Landires, I, Lanfranchi, F, Langguth, B, Lansingh, V, Laplante-Lévesque, A, Larijani, B, Larsson, A, Lasrado, S, Lauriola, P, Le, H, Le, L, Le, N, Le, T, Leasher, J, Ledda, C, Lee, M, Lee, P, Lee, S, Lee, Y, Legrand, K, Leigh, J, Leong, E, Lerango, T, Lescinsky, H, Leung, J, Li, M, Li, W, Li, Y, Li, Z, Ligade, V, Lim, L, Lim, S, Lin, R, Lin, S, Liu, C, Liu, G, Liu, J, Liu, R, Liu, S, Liu, W, Liu, X, Livingstone, K, Llanaj, E, Lohiya, A, López-Bueno, R, Lopukhov, P, Lorkowski, S, Lotufo, P, Lozano, R, Lubinda, J, Lucchetti, G, Luo, L, Lv, H, M Amin, H, Ma, Z, Maass, K, Mabrok, M, Machairas, N, Machoy, M, Mafhoumi, A, Magdy Abd El Razek, M, Maghazachi, A, Mahadeshwara Prasad, D, Maharaj, S, Mahmoud, M, Mahmoudi, E, Majeed, A, Makram, O, Makris, K, Malasala, S, Maled, V, Malhotra, K, Malik, A, Malik, I, Malinga, L, Malta, D, Mamun, A, Manda, A, Manla, Y, Mansour, A, Mansouri, B, Mansouri, P, Mansourian, M, Mansournia, M, Mantovani, L, Manu, E, Marateb, H, Maravilla, J, Marsh, E, Martinez, G, Martinez-Piedra, R, Martini, S, Martins-Melo, F, Martorell, M, Marx, W, Maryam, S, Mathangasinghe, Y, Mathioudakis, A, Matozinhos, F, Mattumpuram, J, Maugeri, A, Maulik, P, Mayeli, M, Mazidi, M, Mazzotti, A, Mcgrath, J, Mckee, M, Mckowen, A, 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Mustafa Z, Yousefi, Zabihollah, Yu, Chuanhua, Yu, Yong, Zadey, Siddhesh, Zadnik, Vesna, Zakham, Fathiah, Zaki, Nazar, Zakzuk, Josefina, Zamagni, Giulia, Zaman, Sojib Bin, Zandieh, Ghazal G Z, Zanghì, Aurora, Zar, Heather J, Zare, Iman, Zarimeidani, Fatemeh, Zastrozhin, Mikhail Sergeevich, Zeng, Youjie, Zhai, Chunxia, Zhang, Anthony Lin, Zhang, Haijun, Zhang, Liqun, Zhang, Meixin, Zhang, Yunquan, Zhang, Zhenyu, Zhang, Zhi-Jiang, Zhao, Hanqing, Zhao, Jeff T, Zhao, Xiu-Ju George, Zhao, Yang, Zhao, Yong, Zhong, Chenwen, Zhou, Jingjing, Zhou, Juexiao, Zhou, Shangcheng, Zhu, Bin, Zhu, Lei, Zhu, Zhaohua, Ziaeian, Boback, Ziafati, Makan, Zielińska, Magdalena, Zimsen, Stephanie R M, Zoghi, Ghazal, Zoller, Thomas, Zumla, Alimuddin, Zyoud, Sa'ed H, Zyoud, Samer H, Murray, Christopher J L, and Gakidou, Emmanuela
- Abstract
Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk
- Published
- 2024
8. Factors associated with variations in hospital expenditures for acute heart failure in the United States
- Author
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Ziaeian, B, Sharma, PP, Yu, TC, Johnson, KW, and Fonarow, GC
- Subjects
Cardiovascular Medicine And Haematology ,Public Health And Health Services ,Cardiovascular System & Hematology ,Cardiorespiratory Medicine and Haematology ,Public Health and Health Services - Abstract
Background Relatively little contemporary data are available that describe differences in acute heart failure (AHF) hospitalization expenditures as a function of patient and hospital characteristics, especially from a population-based investigation. This study aimed to evaluate factors associated with variations in hospital expenditures for AHF in the United States. Methods A cross-sectional analysis using discharge data from the 2011 Nationwide Inpatient Sample, Healthcare Cost and Utilization Project, was conducted. Discharges with primary International Classification of Diseases, Ninth Revision, Clinical Modification, diagnosis codes for AHF in adults were included. Costs were estimated by converting Nationwide Inpatient Sample charge data using the Healthcare Cost and Utilization Project Cost-to-Charge Ratio File. Discharges with highest (≥80th percentile) versus lowest (≤20th percentile) costs were compared for patient characteristics, hospital characteristics, utilization of procedures, and outcomes. Results Of the estimated 1 million AHF hospital discharges, the mean cost estimates were $10,775 per episode. Younger age, higher percentage of obesity, atrial fibrillation, pulmonary disease, fluid/electrolyte disturbances, renal insufficiency, and greater number of cardiac/noncardiac procedures were observed in stays with highest versus lowest costs. Highest-cost discharges were more likely to be observed in urban and teaching hospitals. Highest-cost AHF discharges also had 5 times longer length of stay, were 9 times more costly, and had higher in-hospital mortality (5.6% vs 3.5%) compared with discharges with lowest costs (all P ;lt). Conclusions Acute heart failure hospitalizations are costly. Expenditures vary markedly among AHF hospitalizations in the United States, with substantial differences in patient and hospital characteristics, procedures, and in-hospital outcomes among discharges with highest compared with lowest costs.
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- 2015
9. Heart failure: Heart failure clinical trials: how do we define success?
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Ziaeian, B and Fonarow, GC
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Cardiorespiratory Medicine and Haematology ,Cardiovascular System & Hematology - Published
- 2013
10. Incidence of Myocardial Infarction After High-Risk Vascular Operations in Adults
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Juo, Y. Y., Mantha, A., Ebrahimi, A., Ziaeian, B., and Benharash, P.
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- 2017
- Full Text
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11. Global, regional, and country-specific lifetime risks of stroke, 1990 and 2016
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Feigin V, Nguyen G, Cercy K, Johnson C, Alam T, Parmar P, Abajobir A, Abate K, Abd-Allah F, Abejie A, Abyu G, Ademi Z, Agarwal G, Ahmed M, Akinyemi R, Al-Raddadi R, Aminde L, Amlie-Lefond C, Ansari H, Asayesh H, Asgedom S, Atey T, Ayele H, Banach M, Banerjee A, Barac A, Barker-Collo S, Barnighausen T, Barregard L, Basu S, Bedi N, Behzadifar M, Bejot Y, Bennett D, Bensenor I, Berhe D, Boneya D, Brainin M, Campos-Nonato I, Caso V, Castaneda-Orjuela C, Rivas J, Catala-Lopez F, Christensen H, Criqui M, Damasceno A, Dandona L, Dandona R, Davletov K, de Courten B, deVeber G, Dokova K, Edessa D, Endres M, Faraon E, Farvid M, Fischer F, Foreman K, Forouzanfar M, Gall S, Gebrehiwot T, Geleijnse J, Gillum R, Giroud M, Goulart A, Gupta R, Hachinski V, Hamadeh R, Hankey G, Hareri H, Havmoeller R, Hay S, Hegazy M, Hibstu D, James S, Jeemon P, John D, Jonas J, Jozwiak J, Kalani R, Kandel A, Kasaeian A, Kengne A, Khader Y, Khan A, Khang Y, Khubchandani J, Kim D, Kim Y, Kivimaki M, Kokubo Y, Kolte D, Kopec J, Kosen S, Kravchenko M, Krishnamurthi R, Kumar G, Lafranconi A, Lavados P, Legesse Y, Li Y, Liang X, Lo W, Lorkowski S, Lotufo P, Loy C, Mackay M, Abd El Razek H, Mahdavi M, Majeed A, Malekzadeh R, Malta D, Mamun A, Mantovani L, Martins S, Mate K, Mazidi M, Mehata S, Meier T, Melaku Y, Mendoza W, Mensah G, Meretoja A, Mezgebe H, Miazgowski T, Miller T, Ibrahim N, Mohammed S, Mokdad A, Moosazadeh M, Moran A, Musa K, Negoi R, Nguyen M, Nguyen Q, Nguyen T, Tran T, Ningrum D, Norrving B, Noubiap J, O'Donnell M, Olagunju A, Onuma O, Owolabi M, Parsaeian M, Patton G, Piradov M, Pletcher M, Pourmalek F, Prakash V, Qorbani M, Rahman M, Rai R, Ranta A, Rawaf D, Rawaf S, Renzaho A, Robinson S, Sahathevan R, Sahebkar A, Salomon J, Santalucia P, Santos I, Sartorius B, Schutte A, Sepanlou S, Shafieesabet A, Shaikh M, Shamsizadeh M, Sheth K, Sisay M, Shin M, Shiue I, Silva D, Sobngwi E, Soljak M, Sorensen R, Sposato L, Stranges S, Suliankatchi R, Tabares-Seisdedos R, Tanne D, Nguyen C, Thakur J, Thrift A, Tirschwell D, Topor-Madry R, Tran B, Nguyen L, Truelsen T, Tsilimparis N, Tyrovolas S, Ukwaja K, Uthman O, Varakin Y, Vasankari T, Venketasubramanian N, Vlassov V, Wang W, Werdecker A, Wolfe C, Xu G, Yano Y, Yonemoto N, Yu C, Zaidi Z, Zaki M, Zhou M, Ziaeian B, Zipkin B, Vos T, Naghavi M, Murray C, Roth G, GBD 2016 Lifetime Risk Stroke, Roth, G, Feigin, V, Nguyen, G, Cercy, K, Johnson, C, Alam, T, Parmar, P, Abajobir, A, Abate, K, Abd-Allah, F, Abejie, A, Abyu, G, Ademi, Z, Agarwal, G, Ahmed, M, Akinyemi, R, Al-Raddadi, R, Aminde, L, Amlie-Lefond, C, Ansari, H, Asayesh, H, Asgedom, S, Atey, T, Ayele, H, Banach, M, Banerjee, A, Barac, A, Barker-Collo, S, Bärnighausen, T, Barregard, L, Basu, S, Bedi, N, Behzadifar, M, Béjot, Y, Bennett, D, Bensenor, I, Berhe, D, Boneya, D, Brainin, M, Campos-Nonato, I, Caso, V, Castañeda-Orjuela, C, Rivas, J, Catalá-López, F, Christensen, H, Criqui, M, Damasceno, A, Dandona, L, Dandona, R, Davletov, K, de Courten, B, Deveber, G, Dokova, K, Edessa, D, Endres, M, Faraon, E, Farvid, M, Fischer, F, Foreman, K, Forouzanfar, M, Gall, S, Gebrehiwot, T, Geleijnse, J, Gillum, R, Giroud, M, Goulart, A, Gupta, R, Hachinski, V, Hamadeh, R, Hankey, G, Hareri, H, Havmoeller, R, Hay, S, Hegazy, M, Hibstu, D, James, S, Jeemon, P, John, D, Jonas, J, Jóźwiak, J, Kalani, R, Kandel, A, Kasaeian, A, Kengne, A, Khader, Y, Khan, A, Khang, Y, Khubchandani, J, Kim, D, Kim, Y, Kivimaki, M, Kokubo, Y, Kolte, D, Kopec, J, Kosen, S, Kravchenko, M, Krishnamurthi, R, Anil Kumar, G, Lafranconi, A, Lavados, P, Legesse, Y, Li, Y, Liang, X, Lo, W, Lorkowski, S, Lotufo, P, Loy, C, Mackay, M, Abd El Razek, H, Mahdavi, M, Majeed, A, Malekzadeh, R, Malta, D, Mamun, A, Mantovani, L, Martins, S, Mate, K, Mazidi, M, Mehata, S, Meier, T, Melaku, Y, Mendoza, W, Mensah, G, Meretoja, A, Mezgebe, H, Miazgowski, T, Miller, T, Ibrahim, N, Mohammed, S, Mokdad, A, Moosazadeh, M, Moran, A, Musa, K, Negoi, R, Nguyen, M, Nguyen, Q, Nguyen, T, Tran, T, Anggraini Ningrum, D, Norrving, B, Noubiap, J, O'Donnell, M, Olagunju, A, Onuma, O, Owolabi, M, Parsaeian, M, Patton, G, Piradov, M, Pletcher, M, Pourmalek, F, Prakash, V, Qorbani, M, Rahman, M, Rai, R, Ranta, A, Rawaf, D, Rawaf, S, Renzaho, A, Robinson, S, Sahathevan, R, Sahebkar, A, Salomon, J, Santalucia, P, Santos, I, Sartorius, B, Schutte, A, Sepanlou, S, Shafieesabet, A, Shaikh, M, Shamsizadeh, M, Sheth, K, Sisay, M, Shin, M, Shiue, I, Silva, D, Sobngwi, E, Soljak, M, Sorensen, R, Sposato, L, Stranges, S, Suliankatchi, R, Tabarés-Seisdedos, R, Tanne, D, Tat Nguyen, C, Thakur, J, Thrift, A, Tirschwell, D, Topor-Madry, R, Tran, B, Nguyen, L, Truelsen, T, Tsilimparis, N, Tyrovolas, S, Ukwaja, K, Uthman, O, Varakin, Y, Vasankari, T, Venketasubramanian, N, Vlassov, V, Wang, W, Werdecker, A, Wolfe, C, Xu, G, Yano, Y, Yonemoto, N, Yu, C, Zaidi, Z, El Sayed Zaki, M, Zhou, M, Ziaeian, B, Zipkin, B, Vos, T, Naghavi, M, Murray, C, Department of Public Health, Clinicum, Neurologian yksikkö, 10922180 - Schutte, Aletta Elisabeth, Feigin, Valery L, Nguyen, Grant, Cercy, Kelly, Johnson, Catherine O, Ahmed, Muktar B, Roth, Gregory A, and GBD 2016 Lifetime Risk of Stroke Collaborators
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Male ,Percentile ,Nutrition and Disease ,Disease ,030204 cardiovascular system & hematology ,Global Health ,Socioeconomic Factor ,Global Burden of Disease ,0302 clinical medicine ,prevention ,Voeding en Ziekte ,Cause of Death ,Global health ,Stroke ,POPULATION ,Cause of death ,Aged, 80 and over ,education.field_of_study ,Incidence (epidemiology) ,Incidence ,Medicine (all) ,11 Medical And Health Sciences ,General Medicine ,Middle Aged ,lifetime risk ,stroke ,3142 Public health care science, environmental and occupational health ,3. Good health ,GBD 2016 Lifetime Risk of Stroke Collaborators ,Female ,BURDEN ,Life Sciences & Biomedicine ,Research Article ,Human ,Adult ,Risk ,Population ,Global Burden of Disease (GBD) ,03 medical and health sciences ,Medicine, General & Internal ,Age Distribution ,General & Internal Medicine ,medicine ,Humans ,Life Science ,Point estimation ,cardiovascular diseases ,Sex Distribution ,education ,VLAG ,Aged ,Science & Technology ,HYPERTENSION ,business.industry ,medicine.disease ,Socioeconomic Factors ,business ,030217 neurology & neurosurgery ,RC ,Demography - Abstract
Background: The lifetime risk of stroke has been calculated in a limited number of selected populations. We sought to estimate the lifetime risk of stroke at the regional, country, and global level using data from a comprehensive study of the prevalence of major diseases.Methods: We used the Global Burden of Disease (GBD) Study 2016 estimates of stroke incidence and the competing risks of death from any cause other than stroke to calculate the cumulative lifetime risks of first stroke, ischemic stroke, or hemorrhagic stroke among adults 25 years of age or older. Estimates of the lifetime risks in the years 1990 and 2016 were compared. Countries were categorized into quintiles of the sociodemographic index (SDI) used in the GBD Study, and the risks were compared across quintiles. Comparisons were made with the use of point estimates and uncertainty intervals representing the 2.5th and 97.5th percentiles around the estimate.Results: The estimated global lifetime risk of stroke from the age of 25 years onward was 24.9% (95% uncertainty interval, 23.5 to 26.2); the risk among men was 24.7% (95% uncertainty interval, 23.3 to 26.0), and the risk among women was 25.1% (95% uncertainty interval, 23.7 to 26.5). The risk of ischemic stroke was 18.3%, and the risk of hemorrhagic stroke was 8.2%. In high-SDI, high-middle–SDI, and low-SDI countries, the estimated lifetime risk of stroke was 23.5%, 31.1% (highest risk), and 13.2% (lowest risk), respectively; the 95% uncertainty intervals did not overlap between these categories. The highest estimated lifetime risks of stroke according to GBD region were in East Asia (38.8%), Central Europe (31.7%), and Eastern Europe (31.6%), and the lowest risk was in eastern sub-Saharan Africa (11.8%). The mean global lifetime risk of stroke increased from 22.8% in 1990 to 24.9% in 2016, a relative increase of 8.9% (95% uncertainty interval, 6.2 to 11.5); the competing risk of death from any cause other than stroke was considered in this calculation.Conclusions: In 2016, the global lifetime risk of stroke from the age of 25 years onward was approximately 25% among both men and women. There was geographic variation in the lifetime risk of stroke, with the highest risks in East Asia, Central Europe, and Eastern Europe. (Funded by the Bill and Melinda Gates Foundation.)
- Published
- 2018
12. Heart Failure With Mid-Range (Borderline) Ejection Fraction: Clinical Implications and Future Directions
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Hsu, JJ, Ziaeian, B, and Fonarow, GC
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Diagnostic Imaging ,Heart Failure ,heart failure with preserved ejection fraction ,Left ,Disease Management ,Stroke Volume ,Cardiorespiratory Medicine and Haematology ,Prognosis ,HFmrEF ,HFpEF ,outcomes ,Cardiovascular ,Ventricular Function, Left ,Heart Disease ,heart failure with borderline ejection fraction ,Clinical Research ,heart failure with mid-range ejection fraction ,Practice Guidelines as Topic ,Humans ,Ventricular Function ,epidemiology ,HFbEF - Abstract
Heart failure (HF) with borderline ejection fraction was first defined in 2013 in the American College of Cardiology/American Heart Association guidelines as the presence of the typical symptoms of HF and a left ventricular ejection fraction (LVEF) of 41% to 49%. In 2016, the European Society of Cardiology specified HF with mid-range ejection fraction (HFmrEF) as LVEF of 40% to 49%. This range of LVEF is less well studied compared with HF with preserved ejection fraction (HFpEF) and HF with reduced ejection fraction (HFrEF). Although there are effective, guideline-directed medical therapies for patients with HFrEF, no therapies thus far show measurable benefit in HFpEF. Patients with HFmrEF have aclinical profile and prognosis that are closer to those of patients with HFpEF than those of HFrEF, with certain distinctions.Whether these patients represent a unique and dynamic HF group that may benefit from targeted therapies known to be beneficial in patients with HFrEF, such as neurohormonal blockade, requires further study. This review summarizes what is known about the clinical epidemiology, pathophysiology, and prognosis for patients with HFmrEF and how these features compare with the more well-studied HF groups. Although recommended treatments currently focus on aggressive management of comorbidities, we summarize the studies that identify a potential signal for beneficial therapies. Future studies are needed to not only better characterize the HFmrEF population but to also determine effective management strategies to reduce the high cardiovascular morbidity and mortality burdenon this phenotype of patients with HF.
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- 2017
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13. Clinical Effectiveness of Hydralazine-Isosorbide Dinitrate in African-American Patients With Heart Failure
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Ziaeian, B, Fonarow, GC, and Heidenreich, PA
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cardiomyopathies ,nitrates ,heart failure ,heart failure with reduced ejection fraction ,hydralazine ,mortality ,race - Published
- 2017
- Full Text
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14. Global, regional, and country-specific lifetime risks of stroke, 1990 and 2016
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Roth, G, Feigin, V, Nguyen, G, Cercy, K, Johnson, C, Alam, T, Parmar, P, Abajobir, A, Abate, K, Abd-Allah, F, Abejie, A, Abyu, G, Ademi, Z, Agarwal, G, Ahmed, M, Akinyemi, R, Al-Raddadi, R, Aminde, L, Amlie-Lefond, C, Ansari, H, Asayesh, H, Asgedom, S, Atey, T, Ayele, H, Banach, M, Banerjee, A, Barac, A, Barker-Collo, S, Bärnighausen, T, Barregard, L, Basu, S, Bedi, N, Behzadifar, M, Béjot, Y, Bennett, D, Bensenor, I, Berhe, D, Boneya, D, Brainin, M, Campos-Nonato, I, Caso, V, Castañeda-Orjuela, C, Rivas, J, Catalá-López, F, Christensen, H, Criqui, M, Damasceno, A, Dandona, L, Dandona, R, Davletov, K, de Courten, B, Deveber, G, Dokova, K, Edessa, D, Endres, M, Faraon, E, Farvid, M, Fischer, F, Foreman, K, Forouzanfar, M, Gall, S, Gebrehiwot, T, Geleijnse, J, Gillum, R, Giroud, M, Goulart, A, Gupta, R, Hachinski, V, Hamadeh, R, Hankey, G, Hareri, H, Havmoeller, R, Hay, S, Hegazy, M, Hibstu, D, James, S, Jeemon, P, John, D, Jonas, J, Jóźwiak, J, Kalani, R, Kandel, A, Kasaeian, A, Kengne, A, Khader, Y, Khan, A, Khang, Y, Khubchandani, J, Kim, D, Kim, Y, Kivimaki, M, Kokubo, Y, Kolte, D, Kopec, J, Kosen, S, Kravchenko, M, Krishnamurthi, R, Anil Kumar, G, Lafranconi, A, Lavados, P, Legesse, Y, Li, Y, Liang, X, Lo, W, Lorkowski, S, Lotufo, P, Loy, C, Mackay, M, Abd El Razek, H, Mahdavi, M, Majeed, A, Malekzadeh, R, Malta, D, Mamun, A, Mantovani, L, Martins, S, Mate, K, Mazidi, M, Mehata, S, Meier, T, Melaku, Y, Mendoza, W, Mensah, G, Meretoja, A, Mezgebe, H, Miazgowski, T, Miller, T, Ibrahim, N, Mohammed, S, Mokdad, A, Moosazadeh, M, Moran, A, Musa, K, Negoi, R, Nguyen, M, Nguyen, Q, Nguyen, T, Tran, T, Anggraini Ningrum, D, Norrving, B, Noubiap, J, O'Donnell, M, Olagunju, A, Onuma, O, Owolabi, M, Parsaeian, M, Patton, G, Piradov, M, Pletcher, M, Pourmalek, F, Prakash, V, Qorbani, M, Rahman, M, Rai, R, Ranta, A, Rawaf, D, Rawaf, S, Renzaho, A, Robinson, S, Sahathevan, R, Sahebkar, A, Salomon, J, Santalucia, P, Santos, I, Sartorius, B, Schutte, A, Sepanlou, S, Shafieesabet, A, Shaikh, M, Shamsizadeh, M, Sheth, K, Sisay, M, Shin, M, Shiue, I, Silva, D, Sobngwi, E, Soljak, M, Sorensen, R, Sposato, L, Stranges, S, Suliankatchi, R, Tabarés-Seisdedos, R, Tanne, D, Tat Nguyen, C, Thakur, J, Thrift, A, Tirschwell, D, Topor-Madry, R, Tran, B, Nguyen, L, Truelsen, T, Tsilimparis, N, Tyrovolas, S, Ukwaja, K, Uthman, O, Varakin, Y, Vasankari, T, Venketasubramanian, N, Vlassov, V, Wang, W, Werdecker, A, Wolfe, C, Xu, G, Yano, Y, Yonemoto, N, Yu, C, Zaidi, Z, El Sayed Zaki, M, Zhou, M, Ziaeian, B, Zipkin, B, Vos, T, Naghavi, M, Murray, C, Roth, Gregory A., Feigin, Valery L., Nguyen, Grant, Cercy, Kelly, Johnson, Catherine O., Alam, Tahiya, Parmar, Priyakumari G., Abajobir, Amanuel A., Abate, Kalkidan H., Abd-Allah, Foad, Abejie, Ayenew N., Abyu, Gebre Y., Ademi, Zanfina, Agarwal, Gina, Ahmed, Muktar B., Akinyemi, Rufus O., Al-Raddadi, Rajaa, Aminde, Leopold N., Amlie-Lefond, Catherine, Ansari, Hossein, Asayesh, Hamid, Asgedom, Solomon W., Atey, Tesfay M., Ayele, Henok T., Banach, Maciej, Banerjee, Amitava, Barac, Aleksandra, Barker-Collo, Suzanne L., Bärnighausen, Till, Barregard, Lars, Basu, Sanjay, Bedi, Neeraj, Behzadifar, Masoud, Béjot, Yannick, Bennett, Derrick A., Bensenor, Isabela M., Berhe, Derbew F., Boneya, Dube J., Brainin, Michael, Campos-Nonato, Ismael R., Caso, Valeria, Castañeda-Orjuela, Carlos A., Rivas, Jacquelin C., Catalá-López, Ferrán, Christensen, Hanne, Criqui, Michael H., Damasceno, Albertino, Dandona, Lalit, Dandona, Rakhi, Davletov, Kairat, de Courten, Barbora, deVeber, Gabrielle, Dokova, Klara, Edessa, Dumessa, Endres, Matthias, Faraon, Emerito J. A., Farvid, Maryam S., Fischer, Florian, Foreman, Kyle, Forouzanfar, Mohammad H., Gall, Seana L., Gebrehiwot, Tsegaye T., Geleijnse, Johanna M., Gillum, Richard F., Giroud, Maurice, Goulart, Alessandra C., Gupta, Rahul, Gupta, Rajeev, Hachinski, Vladimir, Hamadeh, Randah R., Hankey, Graeme J., Hareri, Habtamu A., Havmoeller, Rasmus, Hay, Simon I., Hegazy, Mohamed I., Hibstu, Desalegn T., James, Spencer L., Jeemon, Panniyammakal, John, Denny, Jonas, Jost B., Jóźwiak, Jacek, Kalani, Rizwan, Kandel, Amit, Kasaeian, Amir, Kengne, Andre P., Khader, Yousef S., Khan, Abdur R., Khang, Young-Ho, Khubchandani, Jagdish, Kim, Daniel, Kim, Yun J., Kivimaki, Mika, Kokubo, Yoshihiro, Kolte, Dhaval, Kopec, Jacek A., Kosen, Soewarta, Kravchenko, Michael, Krishnamurthi, Rita, Anil Kumar, G., Lafranconi, Alessandra, Lavados, Pablo M., Legesse, Yirga, Li, Yongmei, Liang, Xiaofeng, Lo, Warren D., Lorkowski, Stefan, Lotufo, Paulo A., Loy, Clement T., Mackay, Mark T., Abd El Razek, Hassan Magdy, Mahdavi, Mahdi, Majeed, Azeem, Malekzadeh, Reza, Malta, Deborah C., Mamun, Abdullah A., Mantovani, Lorenzo G., Martins, Sheila C. O., Mate, Kedar K., Mazidi, Mohsen, Mehata, Suresh, Meier, Toni, Melaku, Yohannes A., Mendoza, Walter, Mensah, George A., Meretoja, Atte, Mezgebe, Haftay B., Miazgowski, Tomasz, Miller, Ted R., Ibrahim, Norlinah M., Mohammed, Shafiu, Mokdad, Ali H., Moosazadeh, Mahmood, Moran, Andrew E., Musa, Kamarul I., Negoi, Ruxandra I., Nguyen, Minh, Nguyen, Quyen L., Nguyen, Trang H., Tran, Tung T., Nguyen, Thanh T., Anggraini Ningrum, Dina Nur, Norrving, Bo, Noubiap, Jean J., O'Donnell, Martin J., Olagunju, Andrew T., Onuma, Oyere K., Owolabi, Mayowa O., Parsaeian, Mahboubeh, Patton, George C., Piradov, Michael, Pletcher, Martin A., Pourmalek, Farshad, Prakash, V., Qorbani, Mostafa, Rahman, Mahfuzar, Rahman, Muhammad A., Rai, Rajesh K., Ranta, Annemarei, Rawaf, David, Rawaf, Salman, Renzaho, Andre M. N., Robinson, Stephen R., Sahathevan, Ramesh, Sahebkar, Amirhossein, Salomon, Joshua A., Santalucia, Paola, Santos, Itamar S., Sartorius, Benn, Schutte, Aletta E., Sepanlou, Sadaf G., Shafieesabet, Azadeh, Shaikh, Masood A., Shamsizadeh, Morteza, Sheth, Kevin N., Sisay, Mekonnen, Shin, Min-Jeong, Shiue, Ivy, Silva, Diego A. S., Sobngwi, Eugene, Soljak, Michael, Sorensen, Reed J. D., Sposato, Luciano A., Stranges, Saverio, Suliankatchi, Rizwan A., Tabarés-Seisdedos, Rafael, Tanne, David, Tat Nguyen, Cuong, Thakur, J. S., Thrift, Amanda G., Tirschwell, David L., Topor-Madry, Roman, Tran, Bach X., Nguyen, Luong T., Truelsen, Thomas, Tsilimparis, Nikolaos, Tyrovolas, Stefanos, Ukwaja, Kingsley N., Uthman, Olalekan A., Varakin, Yuri, Vasankari, Tommi, Venketasubramanian, Narayanaswamy, Vlassov, Vasiliy V., Wang, Wenzhi, Werdecker, Andrea, Wolfe, Charles D. A., Xu, Gelin, Yano, Yuichiro, Yonemoto, Naohiro, Yu, Chuanhua, Zaidi, Zoubida, El Sayed Zaki, Maysaa, Zhou, Maigeng, Ziaeian, Boback, Zipkin, Ben, Vos, Theo, Naghavi, Mohsen, Murray, Christopher J. L., Roth, G, Feigin, V, Nguyen, G, Cercy, K, Johnson, C, Alam, T, Parmar, P, Abajobir, A, Abate, K, Abd-Allah, F, Abejie, A, Abyu, G, Ademi, Z, Agarwal, G, Ahmed, M, Akinyemi, R, Al-Raddadi, R, Aminde, L, Amlie-Lefond, C, Ansari, H, Asayesh, H, Asgedom, S, Atey, T, Ayele, H, Banach, M, Banerjee, A, Barac, A, Barker-Collo, S, Bärnighausen, T, Barregard, L, Basu, S, Bedi, N, Behzadifar, M, Béjot, Y, Bennett, D, Bensenor, I, Berhe, D, Boneya, D, Brainin, M, Campos-Nonato, I, Caso, V, Castañeda-Orjuela, C, Rivas, J, Catalá-López, F, Christensen, H, Criqui, M, Damasceno, A, Dandona, L, Dandona, R, Davletov, K, de Courten, B, Deveber, G, Dokova, K, Edessa, D, Endres, M, Faraon, E, Farvid, M, Fischer, F, Foreman, K, Forouzanfar, M, Gall, S, Gebrehiwot, T, Geleijnse, J, Gillum, R, Giroud, M, Goulart, A, Gupta, R, Hachinski, V, Hamadeh, R, Hankey, G, Hareri, H, Havmoeller, R, Hay, S, Hegazy, M, Hibstu, D, James, S, Jeemon, P, John, D, Jonas, J, Jóźwiak, J, Kalani, R, Kandel, A, Kasaeian, A, Kengne, A, Khader, Y, Khan, A, Khang, Y, Khubchandani, J, Kim, D, Kim, Y, Kivimaki, M, Kokubo, Y, Kolte, D, Kopec, J, Kosen, S, Kravchenko, M, Krishnamurthi, R, Anil Kumar, G, Lafranconi, A, Lavados, P, Legesse, Y, Li, Y, Liang, X, Lo, W, Lorkowski, S, Lotufo, P, Loy, C, Mackay, M, Abd El Razek, H, Mahdavi, M, Majeed, A, Malekzadeh, R, Malta, D, Mamun, A, Mantovani, L, Martins, S, Mate, K, Mazidi, M, Mehata, S, Meier, T, Melaku, Y, Mendoza, W, Mensah, G, Meretoja, A, Mezgebe, H, Miazgowski, T, Miller, T, Ibrahim, N, Mohammed, S, Mokdad, A, Moosazadeh, M, Moran, A, Musa, K, Negoi, R, Nguyen, M, Nguyen, Q, Nguyen, T, Tran, T, Anggraini Ningrum, D, Norrving, B, Noubiap, J, O'Donnell, M, Olagunju, A, Onuma, O, Owolabi, M, Parsaeian, M, Patton, G, Piradov, M, Pletcher, M, Pourmalek, F, Prakash, V, Qorbani, M, Rahman, M, Rai, R, Ranta, A, Rawaf, D, Rawaf, S, Renzaho, A, Robinson, S, Sahathevan, R, Sahebkar, A, Salomon, J, Santalucia, P, Santos, I, Sartorius, B, Schutte, A, Sepanlou, S, Shafieesabet, A, Shaikh, M, Shamsizadeh, M, Sheth, K, Sisay, M, Shin, M, Shiue, I, Silva, D, Sobngwi, E, Soljak, M, Sorensen, R, Sposato, L, Stranges, S, Suliankatchi, R, Tabarés-Seisdedos, R, Tanne, D, Tat Nguyen, C, Thakur, J, Thrift, A, Tirschwell, D, Topor-Madry, R, Tran, B, Nguyen, L, Truelsen, T, Tsilimparis, N, Tyrovolas, S, Ukwaja, K, Uthman, O, Varakin, Y, Vasankari, T, Venketasubramanian, N, Vlassov, V, Wang, W, Werdecker, A, Wolfe, C, Xu, G, Yano, Y, Yonemoto, N, Yu, C, Zaidi, Z, El Sayed Zaki, M, Zhou, M, Ziaeian, B, Zipkin, B, Vos, T, Naghavi, M, Murray, C, Roth, Gregory A., Feigin, Valery L., Nguyen, Grant, Cercy, Kelly, Johnson, Catherine O., Alam, Tahiya, Parmar, Priyakumari G., Abajobir, Amanuel A., Abate, Kalkidan H., Abd-Allah, Foad, Abejie, Ayenew N., Abyu, Gebre Y., Ademi, Zanfina, Agarwal, Gina, Ahmed, Muktar B., Akinyemi, Rufus O., Al-Raddadi, Rajaa, Aminde, Leopold N., Amlie-Lefond, Catherine, Ansari, Hossein, Asayesh, Hamid, Asgedom, Solomon W., Atey, Tesfay M., Ayele, Henok T., Banach, Maciej, Banerjee, Amitava, Barac, Aleksandra, Barker-Collo, Suzanne L., Bärnighausen, Till, Barregard, Lars, Basu, Sanjay, Bedi, Neeraj, Behzadifar, Masoud, Béjot, Yannick, Bennett, Derrick A., Bensenor, Isabela M., Berhe, Derbew F., Boneya, Dube J., Brainin, Michael, Campos-Nonato, Ismael R., Caso, Valeria, Castañeda-Orjuela, Carlos A., Rivas, Jacquelin C., Catalá-López, Ferrán, Christensen, Hanne, Criqui, Michael H., Damasceno, Albertino, Dandona, Lalit, Dandona, Rakhi, Davletov, Kairat, de Courten, Barbora, deVeber, Gabrielle, Dokova, Klara, Edessa, Dumessa, Endres, Matthias, Faraon, Emerito J. A., Farvid, Maryam S., Fischer, Florian, Foreman, Kyle, Forouzanfar, Mohammad H., Gall, Seana L., Gebrehiwot, Tsegaye T., Geleijnse, Johanna M., Gillum, Richard F., Giroud, Maurice, Goulart, Alessandra C., Gupta, Rahul, Gupta, Rajeev, Hachinski, Vladimir, Hamadeh, Randah R., Hankey, Graeme J., Hareri, Habtamu A., Havmoeller, Rasmus, Hay, Simon I., Hegazy, Mohamed I., Hibstu, Desalegn T., James, Spencer L., Jeemon, Panniyammakal, John, Denny, Jonas, Jost B., Jóźwiak, Jacek, Kalani, Rizwan, Kandel, Amit, Kasaeian, Amir, Kengne, Andre P., Khader, Yousef S., Khan, Abdur R., Khang, Young-Ho, Khubchandani, Jagdish, Kim, Daniel, Kim, Yun J., Kivimaki, Mika, Kokubo, Yoshihiro, Kolte, Dhaval, Kopec, Jacek A., Kosen, Soewarta, Kravchenko, Michael, Krishnamurthi, Rita, Anil Kumar, G., Lafranconi, Alessandra, Lavados, Pablo M., Legesse, Yirga, Li, Yongmei, Liang, Xiaofeng, Lo, Warren D., Lorkowski, Stefan, Lotufo, Paulo A., Loy, Clement T., Mackay, Mark T., Abd El Razek, Hassan Magdy, Mahdavi, Mahdi, Majeed, Azeem, Malekzadeh, Reza, Malta, Deborah C., Mamun, Abdullah A., Mantovani, Lorenzo G., Martins, Sheila C. O., Mate, Kedar K., Mazidi, Mohsen, Mehata, Suresh, Meier, Toni, Melaku, Yohannes A., Mendoza, Walter, Mensah, George A., Meretoja, Atte, Mezgebe, Haftay B., Miazgowski, Tomasz, Miller, Ted R., Ibrahim, Norlinah M., Mohammed, Shafiu, Mokdad, Ali H., Moosazadeh, Mahmood, Moran, Andrew E., Musa, Kamarul I., Negoi, Ruxandra I., Nguyen, Minh, Nguyen, Quyen L., Nguyen, Trang H., Tran, Tung T., Nguyen, Thanh T., Anggraini Ningrum, Dina Nur, Norrving, Bo, Noubiap, Jean J., O'Donnell, Martin J., Olagunju, Andrew T., Onuma, Oyere K., Owolabi, Mayowa O., Parsaeian, Mahboubeh, Patton, George C., Piradov, Michael, Pletcher, Martin A., Pourmalek, Farshad, Prakash, V., Qorbani, Mostafa, Rahman, Mahfuzar, Rahman, Muhammad A., Rai, Rajesh K., Ranta, Annemarei, Rawaf, David, Rawaf, Salman, Renzaho, Andre M. N., Robinson, Stephen R., Sahathevan, Ramesh, Sahebkar, Amirhossein, Salomon, Joshua A., Santalucia, Paola, Santos, Itamar S., Sartorius, Benn, Schutte, Aletta E., Sepanlou, Sadaf G., Shafieesabet, Azadeh, Shaikh, Masood A., Shamsizadeh, Morteza, Sheth, Kevin N., Sisay, Mekonnen, Shin, Min-Jeong, Shiue, Ivy, Silva, Diego A. S., Sobngwi, Eugene, Soljak, Michael, Sorensen, Reed J. D., Sposato, Luciano A., Stranges, Saverio, Suliankatchi, Rizwan A., Tabarés-Seisdedos, Rafael, Tanne, David, Tat Nguyen, Cuong, Thakur, J. S., Thrift, Amanda G., Tirschwell, David L., Topor-Madry, Roman, Tran, Bach X., Nguyen, Luong T., Truelsen, Thomas, Tsilimparis, Nikolaos, Tyrovolas, Stefanos, Ukwaja, Kingsley N., Uthman, Olalekan A., Varakin, Yuri, Vasankari, Tommi, Venketasubramanian, Narayanaswamy, Vlassov, Vasiliy V., Wang, Wenzhi, Werdecker, Andrea, Wolfe, Charles D. A., Xu, Gelin, Yano, Yuichiro, Yonemoto, Naohiro, Yu, Chuanhua, Zaidi, Zoubida, El Sayed Zaki, Maysaa, Zhou, Maigeng, Ziaeian, Boback, Zipkin, Ben, Vos, Theo, Naghavi, Mohsen, and Murray, Christopher J. L.
- Abstract
BACKGROUND The lifetime risk of stroke has been calculated in a limited number of selected populations. We sought to estimate the lifetime risk of stroke at the regional, country, and global level using data from a comprehensive study of the prevalence of major diseases. METHODS We used the Global Burden of Disease (GBD) Study 2016 estimates of stroke incidence and the competing risks of death from any cause other than stroke to calculate the cumulative lifetime risks of first stroke, ischemic stroke, or hemorrhagic stroke among adults 25 years of age or older. Estimates of the lifetime risks in the years 1990 and 2016 were compared. Countries were categorized into quintiles of the sociodemographic index (SDI) used in the GBD Study, and the risks were compared across quintiles. Comparisons were made with the use of point estimates and uncertainty intervals representing the 2.5th and 97.5th percentiles around the estimate. RESULTS The estimated global lifetime risk of stroke from the age of 25 years onward was 24.9% (95% uncertainty interval, 23.5 to 26.2); the risk among men was 24.7% (95% uncertainty interval, 23.3 to 26.0), and the risk among women was 25.1% (95% uncertainty interval, 23.7 to 26.5). The risk of ischemic stroke was 18.3%, and the risk of hemorrhagic stroke was 8.2%. In high-SDI, high-middle-SDI, and low- SDI countries, the estimated lifetime risk of stroke was 23.5%, 31.1% (highest risk), and 13.2% (lowest risk), respectively; the 95% uncertainty intervals did not overlap between these categories. The highest estimated lifetime risks of stroke according to GBD region were in East Asia (38.8%), Central Europe (31.7%), and Eastern Europe (31.6%), and the lowest risk was in eastern sub-Saharan Africa (11.8%). The mean global lifetime risk of stroke increased from 22.8% in 1990 to 24.9% in 2016, a relative increase of 8.9% (95% uncertainty interval, 6.2 to 11.5); the competing risk of death from any cause other than stroke was considered in this calcul
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- 2018
15. Short-term Outcome of Early Tracheostomy in the Trauma Patients Admitted to Intensive Care Unit: A Comparative Study
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Ziaeian B, Tahmasebi S, mohammadhadi niakan, and Fazelzadeh A
16. Tube Thoracostomy (Chest Tube) Removal in Traumatic Patients: What Do We Know? What Can We Do?
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Paydar S, Ghahramani Z, Ghoddusi Johari H, Khezri S, Ziaeian B, Ma, Ghayyoumi, Mohammad Javad Fallahi, Mh, Niakan, Sabetian G, Hr, Abbasi, and Bolandparvaz S
17. Diagnosing myocardial contusion after blunt chest trauma
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Alborzi, Z., Zangouri, V., Shahram Paydar, Ghahramani, Z., Shafa, M., Ziaeian, B., Radpey, M. R., Amirian, A., and Khodaei, S.
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lcsh:Diseases of the circulatory (Cardiovascular) system ,Thoracic injuries • Contusion • Diagnose ,Diagnose ,lcsh:RC666-701 ,Thoracic injuries ,Review Article ,Contusion - Abstract
A myocardial contusion refers to a bruise of the cardiac muscle, the severity of which can vary depending on the severity of the injury and when the injury occurs. It is a major cause of rapid death which happens after blunt chest trauma and should be suspected at triage in the emergency department. We demonstrated that suspected myocardial contusion patients who have normal electrocardiograms (ECGs) and biomarker tests can be safely discharged. However, if the test results are abnormal, the next steps should be echocardiography and more advanced measures. Diagnosing myocardial contusion is very difficult because of its nonspecific symptoms. If a myocardial contusion happens, cardiogenic shock or arrhythmia must be anticipated, and the patient must be carefully monitored.
18. What is your diagnosis? See the next page for your diagnosis
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Ziaeian, B., Mohammad Yasin Karami, and Sahafi, S. M.
19. National Costs for Cardiovascular-Related Hospitalizations and Inpatient Procedures in the United States, 2016 to 2021.
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Haidar A, Gajjar A, Parikh RV, Benharash P, Fonarow GC, Watson K, Needleman J, and Ziaeian B
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- Humans, United States epidemiology, Retrospective Studies, Female, Male, Health Care Costs trends, Health Care Costs statistics & numerical data, Aged, Middle Aged, Inpatients, Hospital Costs trends, Hospital Costs statistics & numerical data, Hospitalization economics, Cardiovascular Diseases therapy, Cardiovascular Diseases economics, Cardiovascular Diseases epidemiology
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The current economic burden of cardiovascular (CV)-related hospitalizations grouped by diagnoses and procedures in the United States has not been well characterized. The objective was to identify current trends in CV-related hospitalizations, procedural utilization, and health care costs using the most recent 6 years of hospitalization data. A retrospective analysis of discharge data from the National Inpatient Sample database was conducted to determine trends in CV-related hospitalizations, costs, and procedures for each year from 2016 to the most recent available dataset, 2021. Total CV-related costs were adjusted to and reported in 2023 dollars. In 2021, there were 4,687,370 CV-related hospitalizations at a cost of $108 billion. Heart failure hospitalizations accounted for the highest costs at $18.5 billion, followed by non-ST-elevation myocardial infarction at $11.2 billion and stroke at $10.9 billion. Significant upward trends in costs from 2016 to 2021 were observed for heart failure, stroke, atrial fibrillation, ST-elevation myocardial infarction, chest pain, hypertensive emergency, ventricular tachycardia, aortic dissection, sudden cardiac death, pericarditis, supraventricular tachycardia, and pulmonary heart disease. Over the 6 observational years, total costs increased by over $10 billion, representing a 10% increase. However, the increases were not linear, as there was a significant increase of 6.5% from 2018 to 2019, then a decrease of over 7% from 2019 to 2020, followed by an increase of approximately 6% from 2020 to 2021. By 2030, total CV-related costs are projected to reach $131.3 billion. For all years, coronary procedures were the most performed, followed by extracorporeal membrane oxygenation, non-bypass peripheral vascular surgery, pacemaker placement, and coronary artery bypass graft surgery. Both transcatheter aortic valve replacement and MitraClip procedures demonstrated significant upward trends from 2016 to 2021. Overall, from the years 2016 to 2021, CV-related hospitalizations, costs, and procedures demonstrated upward trends. In conclusion, CV disease remains a high burden in the hospital setting with tremendous health care costs., Competing Interests: Declaration of competing interest Dr. Parikh receives unrelated research support from Bayer, Infraredx (Nipro), and Abbott Vascular, and consulting fees from Abbott Vascular. Dr. Fonarow reports consulting for Abbott, Amgen, AstraZeneca, Bayer, Boehinger Ingelheim, Cytokinetics, Eli Lilly, Johnson & Johnson, Medtronic, Merck, Novartis, and Pfizer. Dr. Benharash received proctoring fees from AtriCure Inc. The remaining authors have no competing interests to declare., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)
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- 2025
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20. Clinical Characteristics and Current Management of U.S. Adults at Elevated Risk for Heart Failure Using the PREVENT Equations: A Cross-Sectional Analysis.
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Sussman JB, Wilson LM, Burke JF, Ziaeian B, and Anderson TS
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Competing Interests: Disclosures: Disclosure forms are available with the article online.
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- 2025
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21. HF STATS 2024: Heart Failure Epidemiology and Outcomes Statistics An Updated 2024 Report from the Heart Failure Society of America.
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Bozkurt B, Ahmad T, Alexander K, Baker WL, Bosak K, Breathett K, Carter S, Drazner MH, Dunlay SM, Fonarow GC, Greene SJ, Heidenreich P, Ho JE, Hsich E, Ibrahim NE, Jones LM, Khan SS, Khazanie P, Koelling T, Lee CS, Morris AA, Page RL 2nd, Pandey A, Piano MR, Sandhu AT, Stehlik J, Stevenson LW, Teerlink J, Vest AR, Yancy C, and Ziaeian B
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- 2025
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22. National Trends in Heart Failure Hospitalizations and Readmissions From 2010 to 2021.
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Agarwal MA, Fonarow GC, and Ziaeian B
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- 2025
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23. Global Impact of Optimal Implementation of Guideline-Directed Medical Therapy in Heart Failure.
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Tang AB, Ziaeian B, Butler J, Yancy CW, and Fonarow GC
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- Humans, Practice Guidelines as Topic, Sodium-Glucose Transporter 2 Inhibitors therapeutic use, Angiotensin Receptor Antagonists therapeutic use, Angiotensin-Converting Enzyme Inhibitors therapeutic use, Global Health, Guideline Adherence, Female, Male, Neprilysin antagonists & inhibitors, Heart Failure drug therapy, Heart Failure mortality, Stroke Volume, Adrenergic beta-Antagonists therapeutic use, Mineralocorticoid Receptor Antagonists therapeutic use
- Abstract
Importance: Guideline-directed medical therapy (GDMT) remains underutilized on a global level, with significant disparities in access to treatment worldwide. The potential global benefits of quadruple therapy on patients with heart failure with reduced ejection fraction (HFrEF) have not yet been estimated., Objective: To assess the projected population-level benefit of optimal GDMT use globally among patients with HFrEF., Design, Setting, and Participants: Estimates for HFrEF prevalence, contraindications to GDMT, treatment rates, and the number needed to treat for all-cause mortality at 12 months were derived from previously published sources. Potential lives saved from optimal implementation of quadruple therapy among patients with HFrEF was calculated globally and a sensitivity analysis was conducted to account for uncertainty in the existing data., Main Outcomes and Measures: All-cause mortality., Results: Of an estimated 28.89 million people with HFrEF worldwide, there were 8 235 063 (95% CI, 6 296 020-10 762 972) potentially eligible for but not receiving β-blockers, 20 387 000 (95% CI, 15 867 004-26 184 996) eligible for but not receiving angiotensin receptor-neprilysin inhibitors, 12 223 700 (95% CI, 9 376 895-15 924 973) eligible for but not receiving mineralocorticoid receptor antagonists, and 21 229 170 (95% CI, 16 537 400-27 242 688) eligible for but not receiving sodium glucose cotransporter-2 inhibitors. Optimal implementation of quadruple GDMT could potentially prevent 1 188 277 (95% CI, 767 933-1 914 561) deaths over 12 months. A large proportion of deaths averted were projected in Southeast Asia, Eastern Mediterranean and Africa, and the Western Pacific regions., Conclusions and Relevance: Improvement in use of GDMT could result in substantial mortality benefits on a global scale. Significant heterogeneity also exists across regions, which warrants additional study with interventions tailored to country-level differences for optimization of GDMT worldwide.
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- 2024
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24. Sex, Race, and Rural-Urban Disparities in Ventricular Tachycardia Ablations.
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Tang AB, Akinrimisi OP, and Ziaeian B
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- Humans, Female, Male, Middle Aged, Aged, United States epidemiology, Sex Factors, Risk Factors, Adult, Tachycardia, Ventricular surgery, Tachycardia, Ventricular epidemiology, Catheter Ablation statistics & numerical data, Healthcare Disparities statistics & numerical data
- Abstract
Background: Ventricular ablation may be clinically indicated for patients with recurrent ventricular tachycardia (VT) and has been shown to decrease risk of recurrence and overall morbidity. However, the existence of disparities among patients receiving ventricular ablation has not been well characterized., Objectives: In this study, the authors examined patients hospitalized with VT to determine whether disparities exist among those receiving ablations., Methods: The authors used the National Inpatient Sample to assess patients hospitalized with a primary diagnosis of VT in 2019 who did and did not receive catheter ablations. Multiple logistic regression was used to calculate risk factors for VT ablation based on age, sex, race/ethnicity, socioeconomic status, and hospital characteristics., Results: After adjusting for baseline characteristics and comorbidities, female and Black patients hospitalized with VT had significantly lower odds of receiving ablations compared with male and White patients (OR: 0.835; 95% CI: 0.699-0.997; P = 0.047; and OR: 0.617; 95% CI: 0.457-0.832; P = 0.002, respectively). Additionally, patients at rural or nonteaching hospitals were significantly less likely to receive ablations compared with those at urban, teaching hospitals. No significant differences were noted based on income or insurance status in the adjusted models., Conclusions: The authors identified significant disparities in the delivery of ventricular ablations among patients hospitalized with VT. Overall, patients who were female or Black as well as those who were hospitalized at rural or nonteaching hospitals were significantly less likely to receive VT ablations during hospitalization., Competing Interests: Funding Support and Author Disclosures Dr Ziaeian is supported by UC END-DISPARITIES grant P50-MD017366, as well as a National Institutes of Health National Center for Advancing Translational Science award (UCLA CTSI UL1TR001881). All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Published by Elsevier Inc.)
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- 2024
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25. Racial and Ethnic Disparities and the National Burden of COVID-19 on Inpatient Hospitalizations: A Retrospective Study in the United States in the Year 2020.
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Nguyen A, Buhr RG, Fonarow GC, Hsu JJ, Brown AF, and Ziaeian B
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Background: Since January 2020, COVID-19 has affected more than 100 million people in the U.S. Previous studies on racial and ethnic disparities related to characteristics and outcomes of COVID-19 patients have been insightful. However, appropriate epidemiologic age-standardization of the disease burden and disparities for hospitalization data are lacking., Objective: To identify and describe racial and ethnic disparities for primary COVID-19 hospitalizations in the U.S. in 2020., Methods: In this nationally representative observational study, we use the National Inpatient Sample to quantify racial and ethnic disparities in COVID-19 hospitalizations. Descriptive statistics for patient characteristics, common comorbidities, age-standardized hospitalization rates, inpatient complications, and mortality among COVID-19 hospitalizations were contrasted by race and ethnicity., Results: There were 1,058,815 primary COVID-19 hospitalizations in 2020. Of those, 47.2% were female, with median age of 66 (IQR, 54, 77). Overall inpatient mortality rate was 11.1%. When compared to White patients, Black, Hispanic, and Native American patients had higher age-standardized hospitalization rate ratios of 2.42 (95% CI 2.40-2.43), 2.26 (2.25-2.28), and 2.51 (2.46-2.56), respectively. Non-White patients had increased age-adjusted rates for procedures and complications. Factors associated with inpatient mortality include age, male sex, Hispanic or Native American race or ethnicity, lower income, Medicaid, heart failure, arrhythmias, coagulopathy, and chronic liver disease., Conclusions: Marginalized populations in the U.S. had over twice the COVID-19 hospitalization rate relative to White patients. Age-adjusted mortality rates were highest for Black, Hispanic, and Native American patients. Careful consideration for vulnerable populations is encouraged during highly communicable respiratory pandemics., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)
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- 2024
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26. 2024 Update to the 2020 ACC/AHA Clinical Performance and Quality Measures for Adults With Heart Failure: A Report of the American Heart Association/American College of Cardiology Joint Committee on Performance Measures.
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Kittleson MM, Breathett K, Ziaeian B, Aguilar D, Blumer V, Bozkurt B, Diekemper RL, Dorsch MP, Heidenreich PA, Jurgens CY, Khazanie P, Koromia GA, and Van Spall HGC
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- Humans, United States, Adult, Heart Failure therapy, American Heart Association, Cardiology standards
- Abstract
This document describes performance measures for heart failure that are appropriate for public reporting or pay-for-performance programs and is meant to serve as a focused update of the "2020 ACC/AHA Clinical Performance and Quality Measures for Adults With Heart Failure: A Report of the American College of Cardiology/American Heart Association Task Force on Performance Measures." The new performance measures are taken from the "2022 AHA/ACC/HFSA Guideline for the Management of Heart Failure: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines" and are selected from the strongest recommendations (Class 1 or Class 3). In contrast, quality measures may not have as much evidence base and generally comprise metrics that might be useful for clinicians and health care organizations for quality improvement but are not yet appropriate for public reporting or pay-for-performance programs. New performance measures include optimal blood pressure control in patients with heart failure with preserved ejection fraction, the use of sodium-glucose cotransporter-2 inhibitors for patients with heart failure with reduced ejection fraction, and the use of guideline-directed medical therapy in hospitalized patients. New quality measures include the use of sodium-glucose cotransporter-2 inhibitors in patients with heart failure with mildly reduced and preserved ejection fraction, the optimization of guideline-directed medical therapy prior to intervention for chronic secondary severe mitral regurgitation, continuation of guideline-directed medical therapy for patients with heart failure with improved ejection fraction, identifying both known risks for cardiovascular disease and social determinants of health, patient-centered counseling regarding contraception and pregnancy risks for individuals with cardiomyopathy, and the need for a monoclonal protein screen to exclude light chain amyloidosis when interpreting a bone scintigraphy scan assessing for transthyretin cardiac amyloidosis., (Copyright © 2024 American College of Cardiology Foundation and the American Heart Association, Inc. Published by Elsevier Inc. All rights reserved.)
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- 2024
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27. Timing of Noncardiac Surgery Following Transcatheter Aortic Valve Replacement: A National Analysis.
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Ebrahimian S, Chervu N, Balian J, Mallick S, Yang EH, Ziaeian B, Aksoy O, and Benharash P
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- Humans, Female, Time Factors, Male, Risk Factors, Aged, Aged, 80 and over, Risk Assessment, Treatment Outcome, United States epidemiology, Retrospective Studies, Patient Readmission, Aortic Valve surgery, Aortic Valve diagnostic imaging, Aortic Valve physiopathology, Surgical Procedures, Operative adverse effects, Transcatheter Aortic Valve Replacement adverse effects, Aortic Valve Stenosis surgery, Aortic Valve Stenosis diagnostic imaging, Aortic Valve Stenosis physiopathology, Databases, Factual, Postoperative Complications epidemiology, Postoperative Complications etiology, Time-to-Treatment
- Abstract
Background: The optimal timing of noncardiac surgery (NCS) following transcatheter aortic valve replacement (TAVR) for aortic stenosis has not been elucidated by current national guidelines., Objectives: The aim of this study was to evaluate the effect of the time interval between TAVR and NCS (Δt) on the perioperative risk of major adverse events (MAEs)., Methods: All adult admissions for isolated TAVR for aortic stenosis were identified in the 2016 to 2020 Nationwide Readmissions Database. Patients who received NCS on subsequent admission were included for analysis and grouped by Δt as follows: ≤30, 31 to 60, 61 to 90, and >90 days. Multivariable regression models were constructed to examine the association of Δt with ensuing outcomes., Results: Of 3,098 patients (median age = 79 years, 41.6% female), 19.1% underwent NCS at ≤30 days, 22.9% at 31 to 60 days, 16.7% at 61 to 90 days, and 41.3% at >90 days. After adjustment, the odds of MAEs were similar for operations performed at ≤30 days (adjusted OR [AOR]: 1.05; 95% CI: 0.74-1.50), 31 to 60 days (AOR: 0.97; 95% CI: 0.71-1.31), and 61 to 90 days (AOR: 0.95; 95% CI: 0.67-1.34), with those at >90 days as reference. When examining the average marginal effect of the interval to surgery, risk-adjusted MAE rates were statistically similar across Δt groups for elective status and NCS risk category combinations., Conclusions: NCS within 30, 31 to 60, or 61 to 90 days after TAVR was not associated with increased odds of MAEs compared with operations after 90 days irrespective of NCS risk category or elective status. Our findings suggest that the interval between NCS and TAVR may not be an accurate predictor of MAE risk in this population., Competing Interests: Funding Support and Author Disclosures Dr Yang has received consulting fees from Edwards Lifesciences; this manuscript does not specifically discuss any Atricure or Edwards Lifesciences services. Dr Benharash has received proctor fees from Atricure. 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.)
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- 2024
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28. Examining Heart Failure Outcomes Amid Housing Insecurity.
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Webb M, Brownell NK, Gabrielian S, Fonarow GC, and Ziaeian B
- Abstract
Background: How housing insecurity might affect patients with heart failure (HF) is not well characterized. Housing insecurity increases risks related to both communicable and noncommunicable diseases. For patients with HF, housing insecurity is likely to increase the risk for worse outcomes and rehospitalizations., Methods and Results: We analyzed hospitalizations due to HF in the United States by using the 2020 National Inpatient Sample and Nationwide Readmissions Database to evaluate the impacts of housing insecurity on HF outcomes and hospital use. Individuals were identified as having housing insecurity by using diagnostic International Classification of Disease (ICD)-10 codes. Demographics and comorbidities were compared between patients with HF with and without housing insecurity. An adjusted logistic regression was performed to evaluate the relationships between housing insecurity and socioeconomic status on in-hospital mortality. Using a Cox proportional hazards model, patients with HF and without housing insecurity were evaluated for the risk of all-cause and HF-specific readmissions over time. Of the 1,003,270 hospitalizations for HF in the U.S. in 2020, 16,150 were identified as having housing insecurity (1.6%), and 987,120 were identified as having no housing insecurity (98.4%). The median age of patients with housing insecurity who were hospitalized for HF was 57, as compared to 73 in the population with no housing insecurity. A higher proportion of patients in the housing-insecurity group were Black (35% vs 20.1%) or Hispanic (11.1% vs 7.3%). Patients with housing insecurity were more likely to carry a diagnosis of alcohol-use disorder (15.2% vs 3.3%) or substance-use disorder (70.2% vs 17.8%) but were less likely to use tobacco (18.3% vs 28.7%). Patients with housing insecurity were over 4.5 times more likely to have Medicaid (52.4% vs 11.3%). Median length of stay did not differ between patients with housing insecurity vs those without it. Patients with housing insecurity were more likely to discharge against medical advice (11.4% vs 2.03%). After adjusting for patients' characteristics, housing insecurity was associated with lower in-hospital mortality rates (OR 0.60, 95% CI 0.39-0.92). Housing insecurity was associated with a higher risk of all-cause readmissions at 180 days (HR 1.13, 95% CI 1.12-1.14). However, there was no significant difference in the risk of HF-specific readmissions at 180 days (HR 1.07, 95% CI 0.998-1.14) CONCLUSIONS: Patients with HF and housing insecurity have distinct demographic characteristics. They are also more likely to be readmitted after their initial hospitalization when compared to those without housing insecurity. Identifying and addressing specific comorbid conditions for patients with housing insecurity who are hospitalized for HF may allow clinicians to provide more focused care, with the goal of preventing morbidity, mortality and unnecessary readmissions., Competing Interests: Disclosures GCF reports consulting for Abbott, Amgen, AstraZeneca, Bayer, Boehinger Ingelheim, Cytokinetics, Eli Lilly, Johnson & Johnson, Medtronic, Merck, Novartis, and Pfizer. All other authors have no conflicts of interest to disclose., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)
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- 2024
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29. Cost-Effectiveness of Medical Therapy for Heart Failure With Mildly Reduced and Preserved Ejection Fraction.
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Dixit NM, Truong KP, Vaduganathan M, Ziaeian B, and Fonarow GC
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- Humans, Male, Female, Aged, United States, Markov Chains, Neprilysin antagonists & inhibitors, Angiotensin Receptor Antagonists therapeutic use, Angiotensin Receptor Antagonists economics, Middle Aged, Drug Therapy, Combination, Heart Failure drug therapy, Heart Failure economics, Heart Failure physiopathology, Stroke Volume physiology, Cost-Benefit Analysis, Sodium-Glucose Transporter 2 Inhibitors therapeutic use, Sodium-Glucose Transporter 2 Inhibitors economics, Mineralocorticoid Receptor Antagonists therapeutic use, Mineralocorticoid Receptor Antagonists economics, Quality-Adjusted Life Years
- Abstract
Background: Three medications are now guideline-recommended treatments for heart failure with mildly reduced or preserved ejection fraction (HFmrEF/HFpEF), however, the cost-effectiveness of these agents in combination has yet to be established., Objectives: The purpose of this study was to determine the cost-effectiveness of mineralocorticoid receptor antagonists (MRA), angiotensin receptor-neprilysin inhibitors (ARNIs), and sodium glucose co-transporter 2 inhibitors (SGLT2is) in individuals with HFmrEF/HFpEF., Methods: Using a 3-state Markov model, we performed a cost-effectiveness study using simulated cohorts of 1,000 patients with HFmrEF and HFpEF. Treatment with 1-, 2-, and 3-drug combinations was modeled. Based on a United States health care sector perspective, outcome data was used to calculate incremental cost-effectiveness ratios (ICERs) in 2023 United States dollars based on a 30-year time horizon., Results: Treatment with MRA, MRA+SGLT2i, and MRA+SGLT2i+ARNI therapy resulted in an increase in life years of 1.04, 1.58, and 1.80 in the HFmrEF subgroup, respectively, and 0.99, 1.54, and 1.77 in the HFpEF subgroup, respectively, compared with placebo. At a yearly cost of $18, MRA therapy resulted in ICERs of $10,000 per quality-adjusted life year (QALY) in both subgroups. The ICER for the addition of SGLT2i therapy ($4,962 per year) was $113,000 per QALY in the HFmrEF subgroup and $141,000 in the HFpEF subgroup. The addition of ARNI therapy ($5,504 per year) resulted in ICERs >$250,000 per QALY in both subgroups. If SGLT2i and ARNI were available at generic pricing the ICERs become <$10,000 per QALY in both EF subgroups. Outcomes were highly sensitive to assumed benefit in cardiovascular death., Conclusions: For patients with heart failure, MRA was of high value, SGLT2i was of intermediate value, and ARNI was of low value in both HFmrEF and HFpEF subgroups. For patients with HFmrEF/HFpEF increased use of MRA and SGLT2i therapies should be encouraged and be accompanied with efforts to lower the cost of SGLT2i and ARNI therapies., Competing Interests: Funding Support and Author Disclosures Dr Fonarow has consulted for Abbott, Amgen, AstraZeneca, Bayer, Cytokinetics, Eli Lilly, Janssen, Medtronic, Merck, Novartis, and Pfizer. Dr Vaduganathan has received research grant support, served on advisory boards, or has had speaker engagements with American Regent, Amgen, AstraZeneca, Bayer AG, Baxter Healthcare, Boehringer Ingelheim, Chiesi, Cytokinetics, Lexicon Pharmaceuticals, Novartis, Novo Nordisk, Pharmacosmos, Relypsa, Roche Diagnostics, Sanofi, and Tricog Health; and participates on clinical trial committees for studies sponsored by AstraZeneca, Galmed, Novartis, Bayer AG, Occlutech, and Impulse Dynamics. 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.)
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- 2024
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30. Trends in Income Inequities in Cardiovascular Health Among US Adults, 1988-2018.
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Brownell NK, Ziaeian B, Jackson NJ, and Richards AK
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- Humans, Middle Aged, United States epidemiology, Female, Male, Adult, Aged, Time Factors, Risk Assessment, Social Determinants of Health trends, Poverty trends, Prevalence, Socioeconomic Factors, Heart Disease Risk Factors, Risk Factors, Health Status, Prognosis, Income trends, Cardiovascular Diseases epidemiology, Cardiovascular Diseases diagnosis, Nutrition Surveys, Health Status Disparities
- Abstract
Background: Mean cardiovascular health has improved over the past several decades in the United States, but it is unclear whether the benefit is shared equitably. This study examined 30-year trends in cardiovascular health using a suite of income equity metrics to provide a comprehensive picture of cardiovascular income equity., Methods: The study evaluated data from the 1988-2018 National Health and Nutrition Examination Survey. Survey groupings were stratified by poverty-to-income ratio (PIR) category, and the mean predicted 10-year risk of a major cardiovascular event or death based on the pooled cohort equations (PCE) was calculated (10-year PCE risk). Equity metrics including the relative and absolute concentration indices and the achievement index-metrics that assess both the prevalence and the distribution of a health measure across different socioeconomic categories-were calculated., Results: A total of 26 633 participants aged 40 to 75 years were included (mean age, 53.0-55.5 years; women, 51.9%-53.0%). From 1988-1994 to 2015-2018, the mean 10-year PCE risk improved from 7.8% to 6.4% ( P <0.05). The improvement was limited to the 2 highest income categories (10-year PCE risk for PIR 5: 7.7%-5.1%, P <0.05; PIR 3-4.99: 7.6%-6.1%, P <0.05). The 10-year PCE risk for the lowest income category (PIR <1) did not significantly change (8.1%-8.7%). In 1988-1994, the 10-year PCE risk for PIR <1 was 6% higher than PIR 5; by 2015-2018, this relative inequity increased to 70% ( P <0.05). When using metrics that account for all income categories, the achievement index improved (8.0%-7.1%, P <0.05); however, the achievement index was consistently higher than the mean 10-year PCE risk, indicating the poor persistently had a greater share of adverse health., Conclusions: In this serial cross-sectional survey of US adults spanning 30 years, the population's mean 10-year PCE risk improved, but the improvement was not felt equally across the income spectrum., Competing Interests: Disclosures All authors have not published, posted, or submitted any related papers from the same study. Dr Richards is an advisor to a fund at the Tides Foundation; he did not receive compensation from the Tides Foundation for this or any other study. The other authors report no conflicts.
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- 2024
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31. Development and Optimization of the Veterans Affairs' National Heart Failure Dashboard for Population Health Management.
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Brownell N, Kay C, Parra D, Anderson S, Ballister B, Cave B, Conn J, Dev S, Kaiser S, ROGERs J, Touloupas AD, Verbosky N, Yassa NM, Young E, and Ziaeian B
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- Humans, Stroke Volume, Prognosis, Reproducibility of Results, Ventricular Function, Left, Heart Failure diagnosis, Heart Failure epidemiology, Heart Failure therapy, Population Health Management, Veterans, Ventricular Dysfunction, Left
- Abstract
Background: In 2020, the Veterans Affairs (VA) health care system deployed a heart failure (HF) dashboard for use nationally. The initial version was notably imprecise and unreliable for the identification of HF subtypes. We describe the development and subsequent optimization of the VA national HF dashboard., Materials and Methods: This study describes the stepwise process for improving the accuracy of the VA national HF dashboard, including defining the initial dashboard, improving case definitions, using natural language processing for patient identification, and incorporating an imaging-quality hierarchy model. Optimization further included evaluating whether to require concurrent ICD-codes for inclusion in the dashboard and assessing various imaging modalities for patient characterization., Results: Through multiple rounds of optimization, the dashboard accuracy (defined as the proportion of true results to the total population) was improved from 54.1% to 89.2% for the identification of HF with reduced ejection fraction (HFrEF) and from 53.9% to 88.0% for the identification of HF with preserved ejection fraction (HFpEF). To align with current guidelines, HF with mildly reduced ejection fraction (HFmrEF) was added to the dashboard output with 88.0% accuracy., Conclusions: The inclusion of an imaging-quality hierarchy model and natural-language processing algorithm improved the accuracy of the VA national HF dashboard. The revised dashboard informatics algorithm has higher use rates and improved reliability for the health management of the population., Competing Interests: Disclosures The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)
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- 2024
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32. Cardiovascular Disease's Lonely Hearts Club.
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Agarwal MA and Ziaeian B
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- Humans, Heart, Mediastinum, Cardiovascular Diseases epidemiology, Cardiovascular System
- Abstract
Competing Interests: Declaration of Competing Interest The authors have no competing interests to declare.
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- 2024
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33. New models for heart failure care delivery.
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Xia J, Brownell NK, Fonarow GC, and Ziaeian B
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- Humans, Inpatients, Dashboard Systems, Minority Groups, Delivery of Health Care, Stroke Volume, Heart Failure diagnosis, Heart Failure epidemiology, Heart Failure therapy
- Abstract
Heart failure (HF) is a common disease with increasing prevalence around the world. There is high morbidity and mortality associated with poorly controlled HF along with increasing costs and strain on healthcare systems due to a high rate of rehospitalization and resource utilization. Despite the establishment of clear evidence-based guideline directed medical therapies (GDMT) proven to improve HF morbidity and mortality, there remains significant clinical inertia to optimizing HF patients on GDMT. Only a minority of HF patients are prescribed on all four classes of GDMT. To bridge the gap between the vulnerable population of HF patients and lifesaving GDMT, HF implementation is of increasing importance. HF implementation involves strategies and techniques to improve GDMT optimization along with other modalities to improve HF management. HF implementation meets patients where they are, including at the time of acute decompensation in the inpatient setting, at the vulnerable discharge stage, and at the chronic management stage in the outpatient setting. Inpatient HF implementation strategies include protocolized rapid titration of GDMT, site-level audit-and-feedback, virtual GDMT optimization teams, and electronic health record notifications and alerts. Discharge HF implementation strategies include education at patient and provider levels, discharge summaries, and HF transitional programs. Outpatient HF implementation strategies include digital innovations such as electronic health record utilization and mobile applications, population level strategies such as registries and clinical dashboards), changes in HF team structure and member roles, remote monitoring with implanted devices and telemonitoring, and hospital at home care model. With a growing population of HF patients, there is an increasing need for novel and creative HF implementation and monitoring methods., Competing Interests: Declaration of competing interest JX has no disclosures; NKB has no disclosures; GCF has consulted for Abbott, Amgen, AstraZeneca, Bayer, Boehinger Ingelheim, Cytokinetics, Eli Lilly, Johnson & Johnson, Medtronic, Merck, Novartis, and Pfizer; BZ has no disclosures., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)
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- 2024
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34. Economic Modeling Analysis of an Intensive GDMT Optimization Program in Hospitalized Heart Failure Patients.
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Dixit NM, Parikh NU, Ziaeian B, and Fonarow GC
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- Humans, Stroke Volume, Hospitalization, Heart Failure diagnosis, Heart Failure drug therapy
- Abstract
Background: The STRONG-HF trial (Safety, Tolerability and Efficacy of Up-Titration of Guideline-Directed Medical Therapies for Acute Heart Failure) demonstrated substantial reductions in the composite of mortality and morbidity over 6 months among hospitalized patients with heart failure (HF) who were randomized to intensive guideline-directed medical therapy (GDMT) optimization compared with usual care. Whether an intensive GDMT optimization program would be cost-effective for patients with HF with reduced ejection fraction is unknown., Methods: Using a 2-state Markov model, we evaluated the effect of an intensive GDMT optimization program on hospitalized patients with HF with reduced ejection fraction. Two population models were created to simulate this intervention, a clinical trial model, based on the participants in the STRONG-HF trial, and a real-world model, based on the Get With The Guidelines-HF registry of patients admitted with worsening HF. We then modeled the effect of a 6-month intensive triple therapy GDMT optimization program comprised of cardiologists, clinical pharmacists, and registered nurses. Hazard ratios from the intervention arm of the STRONG-HF trial were applied to both population models to simulate clinical and financial outcomes of an intensive GDMT optimization program from a US health care sector perspective with a lifetime time horizon. Optimal quadruple GDMT use was also modeled., Results: An intensive GDMT optimization program was extremely cost-effective with incremental cost-effectiveness ratios <$10 000 per quality-adjusted life-year in both models. Optimal quadruple GDMT implementation resulted in the most gains in life-years with incremental cost-effectiveness ratios of $60 000 and $54 000 in the clinical trial and real-world models, respectively., Conclusions: An intensive GDMT optimization program for patients hospitalized with HF with reduced ejection fraction would be cost-effective and result in substantial gains in clinical outcomes, especially with the use of optimal quadruple GDMT. Clinicians, payers, and policymakers should prioritize the creation of such programs., Competing Interests: Disclosures Dr Fonarow has consulted for Abbott, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Cytokinetics, Eli Lilly, Johnson & Johnson, Medtronic, Merck, Novartis, and Pfizer. The other authors report no conflicts.
- Published
- 2023
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35. Geographic Variation in the Quality of Heart Failure Care Among U.S. Veterans.
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Kosaraju RS, Fonarow GC, Ong MK, Heidenreich PA, Washington DL, Wang X, and Ziaeian B
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- Humans, Neprilysin, Stroke Volume, Adrenergic beta-Antagonists therapeutic use, Receptors, Angiotensin, Angiotensin Receptor Antagonists therapeutic use, Heart Failure drug therapy, Heart Failure epidemiology, Veterans, Sodium-Glucose Transporter 2 Inhibitors
- Abstract
Background: The burden of heart failure is growing. Guideline-directed medical therapies (GDMT) reduce adverse outcomes in heart failure with reduced ejection fraction (HFrEF). Whether there is geographic variation in HFrEF quality of care is not well described., Objectives: This study evaluated variation nationally for prescription of GDMT within the Veterans Health Administration., Methods: A cohort of Veterans with HFrEF had their address linked to hospital referral regions (HRRs). GDMT prescription was defined using pharmacy data between July 1, 2020, and July 1, 2021. Within HRRs, we calculated the percentage of Veterans prescribed GDMT and a composite GDMT z-score. National choropleth maps were created to evaluate prescription variation. Associations between GDMT performance and demographic characteristics were evaluated using linear regression., Results: Maps demonstrated significant variation in the HRR composite score and GDMT prescriptions. Within HRRs, the prescription of beta-blockers to Veterans was highest with a median of 80% (IQR: 77.3%-82.2%) followed by angiotensin-converting enzyme inhibitor/angiotensin receptor blocker/angiotensin receptor-neprilysin inhibitors (69.3%; IQR: 66.4%-72.1%), sodium-glucose cotransporter-2 inhibitors (10.3%; IQR: 7.7%-12.8%), mineralocorticoid receptor antagonists (29.2%; IQR: 25.8%-33.9%), and angiotensin receptor-neprilysin inhibitors (12.2%; IQR: 8.6%-15.3%). HRR composite GDMT z-scores were inversely associated with the HRR median Gini coefficient (R = -0.13; P = 0.0218) and the percentage of low-income residents (R = -0.117; P = 0.0413)., Conclusions: Wide geographic differences exist for HFrEF care. Targeted strategies may be required to increase GDMT prescription for Veterans in lower-performing regions, including those affected by income inequality and poverty., Competing Interests: Funding Support and Author Disclosures This project was supported by National Institutes of Health/NCATS UCLA CTSI grant number KL2TR001882 (Bethesda, Maryland) and VA HSR and D (CIN 13-417, Los Angeles, California). The content is solely the responsibility of the authors and does not necessarily represent the official views of National Institutes of Health or VA. Dr Fonarow has received consulting fees from Abbott, Amgen, AstraZeneca, Bayer, Cytokinetics, Edwards, Janssen, Medtronic, Merck, and Novartis. Dr Ong has received royalties from UpToDate. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. All rights reserved.)
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- 2023
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36. Racial/Ethnic Disparities in Outcomes After Percutaneous Coronary Intervention.
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Wang DR, Li J, Parikh RV, Ziaeian B, Aksoy O, Jackson NJ, and Hsu JJ
- Subjects
- Humans, Shock, Cardiogenic, Asian American Native Hawaiian and Pacific Islander, Percutaneous Coronary Intervention, Heart Failure, Acute Coronary Syndrome surgery, Hydroxymethylglutaryl-CoA Reductase Inhibitors therapeutic use
- Abstract
Asian American/Pacific Islanders (AAPIs) and Hispanics are growing minority United States populations, but are poorly represented in the cardiovascular literature. This study examines guideline adherence and outcomes in AAPIs and Hispanics compared with non-Hispanic Whites (NHWs) in a quaternary care center after inpatient percutaneous coronary intervention (PCI). The primary end points were inpatient post-PCI bleed, heart failure, cardiogenic shock, and all-cause mortality, whereas the secondary end point was the prescription rate of post-PCI guideline-directed medical therapy including aspirin, statins, P2Y
12 receptor blockers, and cardiopulmonary rehabilitation. Intergroup differences were assessed through analysis of variance or two-way chi-square tests, and the association of race with binary outcomes was examined through logistic regression with NHW as the reference group. Compared with NHW, AAPIs, and Hispanics had higher odds of diabetes mellitus, and AAPIs had higher odds of hypertension and being on dialysis. Hispanics had higher odds of post-PCI mortality versus NHW, both in acute coronary syndrome (odds ratio [OR] 2.04, p = 0.03) and elective PCI (OR 2.51, p = 0.04). AAPI also trended toward higher mortality than NHW in both categories. AAPIs were found to have higher odds of statin prescription (OR 1.91, p = 0.04). Hispanics had lower odds of ticagrelor prescription versus NHW (OR 0.65, p = 0.04), and AAPIs trended toward such. No differences were found for cardiopulmonary rehabilitation prescriptions in groups. This study suggests that despite quality improvement efforts, disparities remain in postprocedural outcomes in minority groups in comparison with NHW., Competing Interests: Declaration of Competing Interest The authors have no competing interests to declare., (Copyright © 2023 Elsevier Inc. All rights reserved.)- Published
- 2023
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37. Opportunities for Change in Home Health Care in Heart Failure.
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Verma A, Heidenreich PA, and Ziaeian B
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- Humans, Heart Failure therapy, Home Care Services, Telemedicine
- Abstract
Competing Interests: Funding Support and Author Disclosures The authors have reported that they have no relationships relevant to the contents of this paper to disclose.
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- 2023
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38. Heart Failure Epidemiology and Outcomes Statistics: A Report of the Heart Failure Society of America.
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Bozkurt B, Ahmad T, Alexander KM, Baker WL, Bosak K, Breathett K, Fonarow GC, Heidenreich P, Ho JE, Hsich E, Ibrahim NE, Jones LM, Khan SS, Khazanie P, Koelling T, Krumholz HM, Khush KK, Lee C, Morris AA, Page RL 2nd, Pandey A, Piano MR, Stehlik J, Stevenson LW, Teerlink JR, Vaduganathan M, and Ziaeian B
- Subjects
- Humans, Hospitalization, Prevalence, Incidence, Heart Failure epidemiology, Heart Failure therapy
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- 2023
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39. Impact of Age and Variant Time Period on Clinical Presentation and Outcomes of Hospitalized Coronavirus Disease 2019 Patients.
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Srivastava PK, Klomhaus AM, Tehrani DM, Fonarow GC, Ziaeian B, Desai PS, Rafique A, de Lemos J, Parikh RV, and Yang EH
- Abstract
Objective: To evaluate the impact of age and COVID-19 variant time period on morbidity and mortality among those hospitalized with COVID-19., Patients and Methods: Patients from the American Heart Association's Get With The Guidelines COVID-19 cardiovascular disease registry (January 20, 2020-February 14, 2022) were divided into groups based on whether they presented during periods of wild type/alpha, delta, or omicron predominance. They were further subdivided by age (young: 18-40 years; older: more than 40 years), and characteristics and outcomes were compared., Results: The cohort consisted of 45,421 hospitalized COVID-19 patients (wild type/alpha period: 41,426, delta period: 3349, and omicron period: 646). Among young patients (18-40 years), presentation during delta was associated with increased odds of severe COVID-19 (OR, 1.6; 95% CI, 1.3-2.1), major adverse cardiovascular events (MACE) (OR, 1.8; 95% CI, 1.3-2.5), and in-hospital mortality (OR, 2.2; 95% CI, 1.5-3.3) when compared with presentation during wild type/alpha. Among older patients (more than 40 years), presentation during delta was associated with increased odds of severe COVID-19 (OR, 1.2; 95% CI, 1.1-1.3), MACE (OR, 1.5; 95% CI, 1.4-1.7), and in-hospital mortality (OR, 1.4; 95% CI, 1.3-1.6) when compared with wild type/alpha. Among older patients (more than 40 years), presentation during omicron associated with decreased odds of severe COVID-19 (OR, 0.7; 95% CI, 0.5-0.9) and in-hospital mortality (OR, 0.6; 95% CI, 0.5-0.9) when compared with wild type/alpha., Conclusion: Among hospitalized adults with COVID-19, presentation during a time of delta predominance was associated with increased odds of severe COVID-19, MACE, and in-hospital mortality compared with presentation during wild type/alpha. Among older patients (aged more than 40 years), presentation during omicron was associated with decreased odds of severe COVID-19 and in-hospital mortality compared with wild type/alpha., Competing Interests: Dr Fonarow reports consulting for Abbott, Amgen, AstraZeneca, Bayer, Cytokinetics, Edwards, Eli Lilly, Janssen, Medtronic, Merck, and Novartis. Dr Parikh receives research support from the American Heart Association, Janssen, Infraredx, Abbott Vascular, and Bayer, and consulting fees from Abbott Vascular. Dr de Lemos reports consulting income from Eli Lilly, Novo Nordisc, and Astra Zeneca. Dr Yang reports research grants/funding from CSL Behring, Boehringer Ingelheim, Eli Lilly, and Bristol Meyers Squibb, and consulting fees from Pfizer., (© 2023 The Authors.)
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- 2023
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40. DASH-HF Study: A Pragmatic Quality Improvement Randomized Implementation Trial for Patients With Heart Failure With Reduced Ejection Fraction.
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Verma A, Fonarow GC, Hsu JJ, Jackevicius CA, Vaghaiwalla Mody F, Nguyen A, Amidi O, Goldberg S, Vetrivel R, Upparapalli D, Theodoropoulos K, Gregorio S, Chang DS, Bostrom K, Althouse AD, and Ziaeian B
- Subjects
- Humans, Stroke Volume, Quality Improvement, Hospitalization, Heart Failure diagnosis, Heart Failure drug therapy, Ventricular Dysfunction, Left
- Abstract
Background: Heart failure is a prevailing diagnosis of hospitalization and readmission within 6 months, and nearly a quarter of these patients die within a year. Guideline-directed medication therapies reduce risk of mortality by 73% over 2 years; however, the implementation of these therapies to their target dose in clinical practice continues to be challenging. In 2020, the Veterans Affairs (VA) Health Care System developed a HF dashboard to monitor and improve outpatient HF management. The DASH-HF (Dashboard Activated Services and Telehealth for Heart Failure) study is a randomized, pragmatic clinical trial to evaluate proactive dashboard-directed telehealth clinics to improve the use and dosing of guideline-directed medication therapy for patients with heart failure with reduced ejection fraction not on optimal guideline-directed medication therapy within the VA., Methods: Three hundred veterans with heart failure with reduced ejection fraction met inclusion criteria with an optimization potential score (OPS) of 5 or less out of 10, representing nonoptimal guideline-directed medication therapy. The primary outcome was a composite score of guideline-directed medical therapy, the OPS, 6 months after the end of the intervention. Secondary outcomes included active prescriptions for each individual guideline-directed medical therapy class, HF-related hospitalizations, deaths, and clinician time per patient during the intervention clinics., Results: There was no significant difference between the intervention arm and usual care group in the primary outcome (OPS, 2.9; SD=2.1 versus OPS, 2.6, SD=2.1); adjusted mean difference 0.3 (95% CI, -0.1 to 0.7) or in the prespecified secondary outcomes for hospitalization and all-cause mortality for the intervention of proactive dashboard-based clinics., Conclusions: A dashboard-based clinic intervention did not improve the OPS or secondary outcomes of hospitalization and all-cause mortality. There remains a larger opportunity to better target patients and provide more intensive follow-up to further evaluate the utility of proactive dashboard-based clinics for HF management and quality improvement., Registration: URL: https://www., Clinicaltrials: gov; Unique identifier: NCT05001165., Competing Interests: Disclosures Dr Fonarow reports consulting for Abbott, Amgen, AstraZeneca, Bayer, Cytokinetics, Edwards, Janssen, Medtronic, Merck, and Novartis. There are no disclosures for the other authors.
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- 2023
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41. Cost-Effectiveness of Comprehensive Quadruple Therapy for Heart Failure With Reduced Ejection Fraction.
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Dixit NM, Parikh NU, Ziaeian B, Jackson N, and Fonarow GC
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- Humans, United States, Cost-Benefit Analysis, Stroke Volume, Mineralocorticoid Receptor Antagonists therapeutic use, Angiotensin Receptor Antagonists therapeutic use, Angiotensin Receptor Antagonists pharmacology, Angiotensin-Converting Enzyme Inhibitors therapeutic use, Adrenergic beta-Antagonists therapeutic use, Heart Failure drug therapy, Ventricular Dysfunction, Left
- Abstract
Background: Heart failure with reduced ejection fraction (HFrEF) is one of the most costly and deadly chronic disease states. The cost effectiveness of a comprehensive quadruple therapy regimen for HFrEF has not been studied., Objectives: The authors sought to determine the cost-effectiveness of quadruple therapy comprised of beta-blockers, mineralocorticoid receptor antagonists, angiotensin receptor-neprilysin inhibitors, and sodium glucose cotransporter-2 inhibitors vs regimens composed of only beta-blockers, angiotensin-converting enzyme inhibitors, and mineralocorticoid receptor antagonists (triple therapy), and angiotensin-converting enzyme inhibitors and beta-blockers (double therapy)., Methods: Using a 2-state Markov model, the authors performed a cost-effectiveness study using simulated populations of 1,000 patients with HFrEF based on the participants in the PARADIGM-HF (Prospective comparison of ARNI with ACEI to Determine Impact on Global Mortality and morbidity in Heart Failure) trial and compared them by treatment strategy (quadruple therapy vs triple and double therapy) from a United States health care system perspective. The authors also performed 10,000 probabilistic simulations., Results: Treatment with quadruple therapy resulted in an increase of 1.73 and 2.87 life-years compared with triple therapy and double therapy, respectively, and an increase in quality-adjusted life-years of 1.12 and 1.85 years, respectively. The incremental cost-effectiveness ratios of quadruple therapy vs triple therapy and double therapy were $81,000 and $51,081, respectively. In 91.7% and 99.9% of probabilistic simulations quadruple therapy had an incremental cost-effectiveness ratio of <$150,000 compared with triple therapy and double therapy, respectively., Conclusions: At current pricing, the use of quadruple therapy in patients with HFrEF was cost effective compared with triple therapy and double therapy. These findings highlight the need for improved access and optimal implementation of comprehensive quadruple therapy in eligible patients with HFrEF., Competing Interests: Funding Support and Author Disclosures Dr Fonarow has consulted for Abbott, Amgen, AstraZeneca, Bayer, Cytokinetics, Eli Lilly, Janssen, Medtronic, Merck, Novartis, and Pfizer. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2023 American College of Cardiology Foundation. All rights reserved.)
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- 2023
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42. Sex Differences in Outcomes of Percutaneous Pulmonary Artery Thrombectomy in Patients With Pulmonary Embolism.
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Agarwal MA, Dhaliwal JS, Yang EH, Aksoy O, Press M, Watson K, Ziaeian B, Fonarow GC, Moriarty JM, Saggar R, and Channick R
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- Humans, Female, Male, United States epidemiology, Retrospective Studies, Cross-Sectional Studies, Sex Characteristics, Treatment Outcome, Thrombectomy adverse effects, Pulmonary Artery surgery, Pulmonary Embolism epidemiology, Pulmonary Embolism surgery, Pulmonary Embolism etiology
- Abstract
Background: The sex differences in use, safety outcomes, and health-care resource use of patients with pulmonary embolism (PE) undergoing percutaneous pulmonary artery thrombectomy are not well characterized., Research Question: What are the sex differences in outcomes for patients diagnosed with PE who undergo percutaneous pulmonary artery thrombectomy?, Study Design and Methods: This retrospective cross-sectional study used national inpatient claims data to identify patients in the United States with a discharge diagnosis of PE who underwent percutaneous thrombectomy between January 2016 and December 2018. We evaluated the demographics, comorbidities, safety outcomes (in-hospital mortality), and health-care resource use (discharge to home, length of stay, and hospital charges) of patients with PE undergoing percutaneous thrombectomy., Results: Among 1,128,904 patients with a diagnosis of PE between 2016 and 2018, 5,160 patients (0.5%) underwent percutaneous pulmonary artery thrombectomy. When compared with male patients, female patients showed higher procedural bleeding (16.9% vs 11.2%; P < .05), required more blood transfusions (11.9% vs 5.7%; P < .05), and experienced more vascular complications (5.0% vs 1.5%; P < .05). Women experienced higher in-hospital mortality (16.9% vs 9.3%; adjusted OR, 1.9; 95% CI, 1.2-3.0; P = .003) when compared with men. Although length of stay and hospital charges were similar to those of men, women were less likely to be discharged home after surviving hospitalization (47.9% vs 60.3%; adjusted OR, 0.7; 95% CI, 0.50-0.99; P = .04)., Interpretation: In this large nationwide cohort, women with PE who underwent percutaneous thrombectomy showed higher morbidity and in-hospital mortality compared with men., (Copyright © 2022. Published by Elsevier Inc.)
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- 2023
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43. US Surveillance of Acute Ischemic Stroke Patient Characteristics, Care Quality, and Outcomes for 2019.
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Ziaeian B, Xu H, Matsouaka RA, Xian Y, Khan Y, Schwamm LS, Smith EE, and Fonarow GC
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- Humans, Female, United States epidemiology, Aged, Male, Platelet Aggregation Inhibitors therapeutic use, Bayes Theorem, Treatment Outcome, Fibrinolytic Agents therapeutic use, Quality of Health Care, Anticoagulants therapeutic use, Ischemic Stroke, Hydroxymethylglutaryl-CoA Reductase Inhibitors therapeutic use, Stroke epidemiology, Stroke therapy, Stroke diagnosis
- Abstract
Background: The United States lacks a timely and accurate nationwide surveillance system for acute ischemic stroke (AIS). We use the Get With The Guidelines-Stroke registry to apply poststratification survey weights to generate national assessment of AIS epidemiology, hospital care quality, and in-hospital outcomes., Methods: Clinical data from the Get With The Guidelines-Stroke registry were weighted using a Bayesian interpolation method anchored to observations from the national inpatient sample. To generate a US stroke forecast for 2019, we linearized time trend estimates from the national inpatient sample to project anticipated AIS hospital volume, distribution, and race/ethnicity characteristics for the year 2019. Primary measures of AIS epidemiology and clinical care included patient and hospital characteristics, stroke severity, vital and laboratory measures, treatment interventions, performance measures, disposition, and clinical outcomes at discharge., Results: We estimate 552 476 patients with AIS were admitted in 2019 to US hospitals. Median age was 71 (interquartile range, 60-81), 48.8% female. Atrial fibrillation was diagnosed in 22.6%, 30.2% had prior stroke/transient ischemic attack, and 36.4% had diabetes. At baseline, 46.4% of patients with AIS were taking antiplatelet agents, 19.2% anticoagulants, and 46.3% cholesterol-reducers. Mortality was 4.4%, and only 52.3% were able to ambulate independently at discharge. Performance nationally on AIS achievement measures were generally higher than 95% for all measures but the use of thrombolytics within 3 hours of early stroke presentations (81.9%). Additional quality measures had lower rates of receipt: dysphagia screening (84.9%), early thrombolytics by 4.5 hours (79.7%), and statin therapy (80.6%)., Conclusions: We provide timely, reliable, and actionable US national AIS surveillance using Bayesian interpolation poststratification weights. These data may facilitate more targeted quality improvement efforts, resource allocation, and national policies to improve AIS care and outcomes.
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- 2022
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44. SGLT2 Inhibitors in Heart Failure: Early Initiation to Achieve Rapid Clinical Benefits.
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Dixit NM, Ziaeian B, and Fonarow GC
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- Humans, Quality of Life, Stroke Volume, Heart Failure drug therapy, Sodium-Glucose Transporter 2 Inhibitors pharmacology, Sodium-Glucose Transporter 2 Inhibitors therapeutic use
- Abstract
Sodium-glucose cotransporter-2 inhibitors (SGLT2i) are a recent addition to the pillars of medical therapy for heart failure (HF) with reduced ejection fraction, all of which improve quality of life, morbidity, and mortality. These benefits are evident within the first 30 days of initiation. This review discusses the rationale for SGLT2i initiation in simultaneous or in rapid sequence with other guideline-directed medical therapy (GDMT). We also discuss SGLT2i use and early benefits in HF patients with an ejection fraction greater than 40%., (Copyright © 2022 Elsevier Inc. All rights reserved.)
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- 2022
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45. The design of the Dashboard Activated Services and Telehealth for Heart Failure (DASH-HF) study: A pragmatic quality improvement randomized implementation trial for patients with heart failure with reduced ejection fraction.
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Verma A, Fonarow GC, Hsu JJ, Jackevicius CA, Mody FV, Amidi O, Goldberg S, Upparapalli D, Theodoropoulos K, Gregorio S, Chang DS, Bostrom K, Althouse AD, and Ziaeian B
- Subjects
- Hospitalization, Humans, Quality Improvement, Stroke Volume, Heart Failure therapy, Telemedicine
- Abstract
Background: Gaps in the receipt and dosing of guideline-directed medical therapy (GDMT) persist for patients with heart failure with reduced ejection fraction (HFrEF) [1]. In 2020, the Veterans Affairs (VA) developed a heart failure (HF) specific population dashboard to monitor care quality and performance on standard HFrEF performance measures [2]., Methods: The Dashboard Activated Services and Telehealth for HF (DASH-HF) study is a pragmatic randomized quality improvement study designed to evaluate the utility of proactive population management clinics using the VA's HF dashboard to optimize GDMT for patients with HFrEF. Panel management telemedicine clinics incorporated multidisciplinary clinicians to perform chart review and impromptu telephone encounters to evaluate current HFrEF management and opportunities to optimize GDMT. The study will evaluate the efficacy of proactive panel management to usual care at 6 months as quantified by the GDMT optimization potential score. Secondary outcomes include hospitalizations, mortality, and clinician time per intervention. The study completed enrollment and randomization of 300 participants. The intervention was performed from September to December 2021., Conclusion: DASH-HF will contribute to the literature by evaluating use of the existing VA dashboard to identify HF patients with the lowest adherence to GDMT and proactively target this group for the intervention., Registration: https://clinicaltrials.gov/. Unique identifier: NCT05001165., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Published by Elsevier Inc.)
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- 2022
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46. Non-pharmaceutical interventions and covid-19 burden in the United States: retrospective, observational cohort study.
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Ahlers M, Aralis H, Tang W, Sussman JB, Fonarow GC, and Ziaeian B
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Objective: To evaluate the adoption and discontinuation of four broadly used non-pharmaceutical interventions on shifts in the covid-19 burden among US states., Design: Retrospective, observational cohort study., Setting: US state data on covid-19 between 19 January 2020 and 7 March 2021., Participants: US population with a diagnosis of covid-19., Main Outcome Measures: Empirically derived breakpoints in case and mortality velocities (ie, rate of change) were used to identify periods of stable, decreasing, or increasing covid-19 burden. Associations between adoption of non-pharmaceutical interventions and subsequent decreases in case or death rates were estimated by use of generalised linear models accounting for weekly variability across US states. State level case and mortality counts per day were obtained from the Covid-19 Tracking Project. State level policies on non-pharmaceutical interventions included stay-at-home orders, indoor public gathering bans (mild >10 or severe ≤10 people), indoor restaurant dining bans, and public mask mandates. National policies were not included in statistical models., Results: 28 602 830 cases and 511 899 deaths were recorded during the study. Odds of a reduction in covid-19 case velocity increased for stay-at-home orders (odds ratio 2.02, 95% confidence interval 1.63 to 2.52), indoor dining bans (1.62, 1.25 to 2.10), public mask mandates (2.18, 1.47 to 3.23), and severe indoor public gathering bans (1.68, 1.31 to 2.16) in univariate analysis. In mutually adjusted models, odds remained elevated for orders to stay at home (adjusted odds ratio 1.47, 95% confidence interval 1.04 to 2.07) and public mask mandates (2.27, 1.51 to 3.41). Stay-at-home orders (odds ratio 2.00, 95% confidence interval 1.53 to 2.62; adjusted odds ratio 1.89, 95% confidence interval 1.25 to 2.87) was also associated with a greater likelihood of decrease in death velocity in unadjusted and adjusted models., Conclusions: State level non-pharmaceutical interventions used in the US during the covid-19 pandemic, in particular stay-at-home orders, were associated with a decreased covid-19 burden., Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: no support from any organisation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
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- 2022
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47. Expenditure on Heart Failure in the United States: The Medical Expenditure Panel Survey 2009-2018.
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Bhatnagar R, Fonarow GC, Heidenreich PA, and Ziaeian B
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- Adult, Ambulatory Care, Health Expenditures, Hospitalization, Humans, United States epidemiology, Diabetes Mellitus, Type 2, Heart Failure epidemiology, Heart Failure therapy
- Abstract
Background: With rising United States health care expenditure, estimating current spending for patients with heart failure (HF) informs the value of preventative health interventions., Objectives: The purpose of this study was to estimate current health care expenditure growth for patients with HF in the United States., Methods: The authors pooled MEPS (Medical Expenditure Panel Survey) data from 2009-2018 to calculate total HF-related expenditure across clinical settings in the United States. A 2-part model adjusted for demographics, comorbidities, and year was used to estimate annual mean and incremental expenditures associated with HF., Results: In the United States, an average of $28,950 (2018 inflation-adjusted dollars) is spent per year for health care-related expenditure for individuals with HF compared with $5,727 for individuals without HF. After adjusting for demographics and comorbidities, a diagnosis of HF was associated with $3,594 in annual incremental expenditure compared with those without HF. HF-related expenditure increased from $26,864 annual per person in 2009-2010 to $32,955 in 2017-2018, representing a 23% rise over 10 years. In comparison, expenditure on myocardial infarction, type 2 diabetes mellitus, and cancer grew by 16%, 28%, and 16%, respectively. Most of the cost was related to hospitalization: $12,569 per year. Outpatient office-based care and prescription medications saw the greatest growth in cost over the period, 41% and 24%, respectively. Estimated incremental national expenditure for HF per year was $22.3 billion; total annual expenditure for adults with HF was $179.5 billion., Conclusions: HF is a costly condition for which expenditure is growing faster than that of other chronic conditions., Competing Interests: Funding Support and Author Disclosures Dr Fonarow has served as a consultant for Abbott, Amgen, AstraZeneca, Bayer, Cytokinetics, Edwards, Janssen, Medtronic, Merck, and Novartis. Dr Ziaeian’s research is supported by AHA SDG 17SDG33630113 and the National Institutes of Health/National Center for Advancing Translational Science (NCATS) UCLA CTSI grant number KL2TR001882. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Published by Elsevier Inc.)
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- 2022
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48. Global Benefit of SGLT2 Inhibitors in Heart Failure With Reduced Ejection Fraction.
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Brownell NK, Ziaeian B, and Fonarow GC
- Abstract
Competing Interests: Dr Fonarow has been a consultant for Abbott, Amgen, AstraZeneca, Bayer, Cytokinetics, Janssen, Medtronic, Merck, and Novartis. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
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- 2022
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49. Expansion of telemedicine during COVID-19 at a VA specialty clinic.
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Balut MD, Wyte-Lake T, Steers WN, Chu K, Dobalian A, Ziaeian B, Heyworth L, and Der-Martirosian C
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- Ambulatory Care Facilities, Humans, Pandemics, SARS-CoV-2, COVID-19, Telemedicine methods
- Abstract
Background: COVID-19 rapidly accelerated the implementation of telemedicine in U.S. Department of Veterans Affairs (VA) specialty care clinics. This mixed-methods study was conducted at a VA medical center to understand the use of telemedicine, and the barriers and facilitators to its implementation, in cardiology outpatient clinics., Methods: Quantitative analyses modeled monthly trends of telemedicine use over 24-months (March 2019-March 2021) with segmented logistic regression and adjusted for socio-demographic predictors of patient-level telemedicine use. Qualitative interviews were conducted (July-October 2020) with eight cardiology clinicians., Results: At the onset of COVID-19, likelihood of telemedicine use was ∼12 times higher than it was pre-COVID-19 (p < 0.001). White (OR = 1.38, 95% CI:1.23-1.54), married (OR = 1.25, 95% CI:1.11-1.40), Veterans with other health insurance (OR = 1.19, 95% CI:1.06-1.35), were more likely to use telemedicine. Veterans with higher health risk factors were less likely (OR = 0.95, 95% CI:0.93-0.97). Facilitators to rapid expansion of telemedicine included prior telemedicine experience; provider trainings; and staff champions. In contrast, lack of technical support and scheduling grids for virtual visits and patient ability/preference served as barriers., Conclusions: Findings suggest that once mutable barriers were addressed, the medical center was able to expand its telemedicine efforts during COVID-19. Beyond the pandemic, a hybrid of virtual and face-to-face care might be feasible and likely beneficial for healthcare providers and patients in specialty care., Implications: The ability to rapidly transition from in-person to virtual visits can potentially assist with the continuity of care and management of chronic disease during infectious outbreaks and other major disasters that obstruct traditional care models., (Published by Elsevier Inc.)
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- 2022
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50. Factors Associated With High Resource Use in Elective Adult Cardiac Surgery From 2005 to 2016.
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Seo YJ, Sareh S, Hadaya J, Sanaiha Y, Ziaeian B, Shemin RJ, and Benharash P
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- Aged, Aged, 80 and over, Cardiac Surgical Procedures adverse effects, Elective Surgical Procedures adverse effects, Female, Hospital Costs, Humans, Length of Stay economics, Male, Middle Aged, Postoperative Complications epidemiology, Social Class, Time Factors, Cardiac Surgical Procedures economics, Elective Surgical Procedures economics, Health Resources
- Abstract
Background: Lack of consensus remains about factors that may be associated with high resource use (HRU) in adult cardiac surgical patients. This study aimed to identify patient-related, hospital, and perioperative characteristics associated with HRU admissions involving elective cardiac operations., Methods: Data from the National Inpatient Sample was used to identify patients who underwent coronary artery bypass graft, valve replacement, and valve repair operations between 2005 and 2016. Admissions with HRU were defined as those in the highest decile for total hospital costs. Multivariable regressions were used to identify factors associated with HRU., Results: An estimated 1,750,253 hospitalizations coded for elective cardiac operations. The median hospitalization cost was $34,700 (interquartile range, $26,800- to $47,100), with the HRU (N = 175,025) cutoff at $66,029. Although HRU patients comprised 10% of admissions, they accounted for 25% of cumulative costs. On multivariable regression, patient-related characteristics predictive of HRU included female sex, older age, higher comorbidity burden, non-White race, and highest income quartile. Hospital factors associated with HRU were low-volume hospitals for both coronary artery bypass graft and valvular operations. Among postoperative outcomes, mortality, infectious complications, extracorporeal membrane oxygenation use, and hospitalization for more than 8 days were associated with greater odds of HRU., Conclusions: In this nationwide study of elective cardiac surgical patients, several important patient-related and hospital factors, including patients' race, comorbidities, postoperative infectious complications, and low hospital operative volume were identified as predictors of HRU. These highly predictive factors may be used for benchmarking purposes and improvement in surgical planning., (Copyright © 2022 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)
- Published
- 2022
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