[1]

Bragazzi NL, Zhong W, Shu J, Abu Much A, Lotan D, et al. 2021. Burden of heart failure and underlying causes in 195 countries and territories from 1990 to 2017. European Journal of Preventive Cardiology 28(15):1682−1690

doi: 10.1093/eurjpc/zwaa147
[2]

Dokainish H, Teo K, Zhu J, Roy A, AlHabib KF, et al. 2017. Global mortality variations in patients with heart failure: results from the International Congestive Heart Failure (INTER-CHF) prospective cohort study. The Lancet Global Health 5(7):e665−e672

doi: 10.1016/S2214-109X(17)30196-1
[3]

Hassannejad R, Shafie D, Turk-Adawi KI, Hajaj AM, Mehrabani-Zeinabad K, et al. 2023. Changes in the burden and underlying causes of heart failure in the Eastern Mediterranean Region, 1990–2019: an analysis of the Global Burden Of Disease Study 2019. eClinicalMedicine 56:101788

doi: 10.1016/j.eclinm.2022.101788
[4]

Mathers CD, Boerma T, Ma Fat D. 2009. Global and regional causes of death. British Medical Bulletin 92(1):7−32

doi: 10.1093/bmb/ldp028
[5]

Huffman MD and Prabhakaran D. 2010. Heart failure: epidemiology and prevention in India. The National Medical Journal of India 23(5):283−288

[6]

Guo Y, Lip GY, Banerjee A. 2013. Heart failure in East Asia. Current Cardiology Reviews 9(2):112−122

doi: 10.2174/1573403x11309020004
[7]

Zhang Y, Gao C, Greene SJ, Greenberg BH, Butler J, et al. 2023. Clinical performance and quality measures for heart failure management in China: the China-heart Failure Registry Study. ESC Heart Failure 10(1):342−352

doi: 10.1002/ehf2.14184
[8]

Heidenreich PA, Fonarow GC, Opsha Y, Sandhu AT, Sweitzer NK, et al. 2022. Economic issues in heart failure in the United States. Journal of Cardiac Failure 28(3):453−466

doi: 10.1016/j.cardfail.2021.12.017
[9]

Ogah OS, Adebiyi A, Sliwa K. 2019. Heart failure in Subsaharan Africa. In Topics in Heart Failure Management. London: IntechOpen. doi: 10.5772/intechopen.82416

[10]

Grimaldi A, Ammirati E, Karam N, Vermi AC, de Concilio A, et al. 2014. Cardiac surgery for patients with heart failure due to structural heart disease in Uganda: access to surgery and outcomes: cardiovascular topic. Cardiovascular Journal of Africa 25(5):204−211

doi: 10.5830/cvja-2014-034
[11]

Hinton RB, Ware SM. 2017. Heart failure in pediatric patients with congenital heart disease. Circulation Research 120(6):978−994

doi: 10.1161/CIRCRESAHA.116.308996
[12]

Gtif I, Bouzid F, Charfeddine S, Abid L, Kharrat N. 2021. Heart failure disease: an African perspective. Archives of Cardiovascular Diseases 114(10):680−690

doi: 10.1016/j.acvd.2021.07.001
[13]

Tsega TA, Demissei BG. 2018. A systematic review of epidemiology, treatment and prognosis of heart failure in adults in Ethiopia. Journal of Cardiovascular Medicine 19(3):91−97

doi: 10.2459/JCM.0000000000000617
[14]

Mandi DG, Bamouni J, Yaméogo RA, Naïbé DT, Kaboré E, et al. 2020. Spectrum of heart failure in sub-Saharan Africa: data from a tertiary hospital-based registry in the eastern center of Burkina Faso. Pan African Medical Journal 36(1):30

doi: 10.11604/pamj.2020.36.30.19321
[15]

Hussen NM, Workie DL, Biresaw HB. 2022. Survival time to complications of congestive heart failure patients at Felege Hiwot comprehensive specialized referral hospital, Bahir Dar, Ethiopia. PLoS One 17(10):e0276440

doi: 10.1371/journal.pone.0276440
[16]

Techane T, Nigussa E, Lemessa F, Fekadu T. 2022. Factors associated with length of intensive care unit stay following cardiac surgery in cardiac center Ethiopia, Addis Ababa, Ethiopia: institution based cross sectional study. Research Reports in Clinical Cardiology 13:19−29

doi: 10.2147/RRCC.S349038
[17]

Bantie B, Seid A, Kerebeh G, Alebel A, Dessie G. 2022. Loss to follow-up in "test and treat era" and its predictors among HIV-positive adults receiving ART in Northwest Ethiopia: institution-based cohort study. Frontiers in Public Health 10:876430

doi: 10.3389/fpubh.2022.876430
[18]

Alemayehu K, Ayalew Bekele Y, Habte Wurjine T. 2022. Factors associated with depression among heart failure patients at selected public hospitals in Addis Ababa, Ethiopia: a cross sectional study. PLoS Global Public Health 2(8):e0000853

doi: 10.1371/journal.pgph.0000853
[19]

Shen L, Jhund PS, Petrie MC, Claggett BL, Barlera S, et al. 2017. Declining risk of sudden death in heart failure. New England Journal of Medicine 377(1):41−51

doi: 10.1056/NEJMoa1609758
[20]

Ahmad T, Munir A, Bhatti SH, Aftab M, Ali Raza M. 2017. Survival analysis of heart failure patients: a case study. PLoS One 12(7):e0181001

doi: 10.1371/journal.pone.0181001
[21]

Taylor CJ, Ordóñez-Mena JM, Roalfe AK, Lay-Flurrie S, Jones NR, et al. 2019. Trends in survival after a diagnosis of heart failure in the United Kingdom 2000−2017: population based cohort study. BMJ 364:1223

doi: 10.1136/bmj.l223
[22]

Cowie MR, Wood DA, Coats AJ, Thompson SG, Suresh V, et al. 2000. Survival of patients with a new diagnosis of heart failure: a population based study. Heart 83(5):505−510

doi: 10.1136/heart.83.5.505
[23]

Pocock SJ, Ariti CA, McMurray JJV, Maggioni A, Køber L, et al. 2013. Predicting survival in heart failure: a risk score based on 39 372 patients from 30 studies. European Heart Journal 34(19):1404−1413

doi: 10.1093/eurheartj/ehs337
[24]

Jackson M, Atuhaire L, Nsimbe D. 2024. Predicting survival of heart failure patients using the Cox Proportional Hazards Model. Research Square:3993213/v1

doi: 10.21203/rs.3.rs-3993213/v1
[25]

Rocke DM. 2021. The Cox proportional hazards model. https://dmrocke.ucdavis.edu/Class/EPI204-Spring-2021/Lecture10ProportionalHazardsModel.pdf

[26]

Keiding N, Andersen PK, Klein JP. 1997. The role of frailty models and accelerated failure time models in describing heterogeneity due to omitted covariates. Statistics in Medicine 16(2):215−224

doi: 10.1002/(SICI)1097-0258(19970130)16:2<215::AID-SIM481>3.0.CO;2-J
[27]

Moore KL and van der Laan MJ. 2009. Application of time-to-event methods in the assessment of safety in clinical trials. In Design and Analysis of Clinical Trials with Time-to-Event Endpoints, ed. Peace KE. New York: Chapman and Hall/CRC. pp. 473–500 doi: 10.1201/9781420066401

[28]

Prinja S, Gupta N, Verma R. 2010. Censoring in clinical trials: review of survival analysis techniques. Indian Journal of Community Medicine 35(2):217−221

doi: 10.4103/0970-0218.66859
[29]

Caires FB, Reis H, Rodrigues PMM. 2023. Survival of the fittest: tourism exposure and firm survival. Applied Economics 55(60):7150−7177

doi: 10.1080/00036846.2023.2208858
[30]

Choi S, Cho H. 2019. Accelerated failure time models for the analysis of competing risks. Journal of the Korean Statistical Society 48:315−326

doi: 10.1016/j.jkss.2018.10.003
[31]

Gupta RD, Kundu D. 2001. Generalized exponential distribution: different method of estimations. Journal of Statistical Computation and Simulation 69(4):315−337

doi: 10.1080/00949650108812098
[32]

Lai CD, Xie M, Murthy DNP. 2003. A modified weibull distribution. IEEE Transactions on Reliability 52(1):33−37

doi: 10.1109/TR.2002.805788
[33]

Khanal SP, Sreenivas V, Acharya SK. 2014. Accelerated failure time models: an application in the survival of acute liver failure patients in india. International Journal of Science and Research 3(6):161−166

[34]

Jal-Usman EA, Nads AA, Langamin DG. 2022. Accelerated failure time (AFT) model: determining the factors associated in the recovery of patients diagnosed with COVID-19. Advances and Applications in Statistics 79:1−9

doi: 10.17654/0972361722056
[35]

Acquah HDG. 2010. Comparison of Akaike information criterion (AIC) and Bayesian information criterion (BIC) in selection of an asymmetric price relationship. Journal of Development and Agricultural Economics 2010:650D3294276

[36]

Weakliem DL. 1999. A critique of the Bayesian information criterion for model selection. Sociological Methods & Research 27(3):359−397

doi: 10.1177/0049124199027003002
[37]

May S, Hosmer DW. 2003. Hosmer and Lemeshow type goodness-of-fit statistics for the Cox proportional hazards model. Handbook of Statistics 23:383−394

doi: 10.1016/s0169-7161(03)23021-2
[38]

Jin CN, Liu M, Sun JP, Fang F, Wen YN, et al. 2014. The prevalence and prognosis of resistant hypertension in patients with heart failure. PLoS One 9(12):e114958

doi: 10.1371/journal.pone.0114958
[39]

Li G, Cook DJ, Thabane L, Friedrich JO, Crozier TM, et al. 2016. Risk factors for mortality in patients admitted to intensive care units with pneumonia. Respiratory Research 17:80

doi: 10.1186/s12931-016-0397-5
[40]

Materu J, Konje ET, Urassa M, Marston M, Boerma T, et al. 2023. Comparison of survival analysis approaches to modelling age at first sex among youth in Kisesa Tanzania. PLoS One 18(9):e0289942

doi: 10.1371/journal.pone.0289942
[41]

Beri B, Fanta K, Bekele F, Bedada W. 2023. Management, clinical outcomes, and its predictors among heart failure patients admitted to tertiary care hospitals in Ethiopia: prospective observational study. BMC Cardiovascular Disorders 23(1):4

doi: 10.1186/s12872-022-03008-7
[42]

Birhanu A, Ayana GM, Merga BT, Alemu A, Negash B, et al. 2022. Incidence and predictors of organ failure among COVID-19 hospitalized adult patients in Eastern Ethiopia. Hospital-based retrospective cohort study. BMC Infectious Diseases 22(1):412

doi: 10.1186/s12879-022-07402-6
[43]

Birlie TA, Amare AT, Agegn SB, Yirga GK, Bantie B, et al. 2024. Treatment seeking delay and associated factors in adult heart failure patients admitted to Debre Tabor comprehensive specialized hospital, North West, Ethiopia. Heliyon 10(1):e23348

doi: 10.1016/j.heliyon.2023.e23348
[44]

Niriayo YL, Yemane B, Asgedom SW, Teklay G, Gidey K. 2024. Prevalence and predictors of poor self-care behaviors in patients with chronic heart failure. Scientific Reports 14(1):1984

doi: 10.1038/s41598-024-52611-5
[45]

Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, et al. 2024. 2024 heart disease and stroke statistics: a report of US and global data from the American Heart Association. Circulation 149(8):e347−e913

doi: 10.1161/CIR.0000000000001209
[46]

Ashine T, Tadesse Likassa H, Chen DG. 2024. Estimating time-to-death and determining risk predictors for heart failure patients: Bayesian AFT shared frailty models with the INLA method. Stats 7(3):1066−1083

doi: 10.3390/stats7030063