Objective: The objectives of the study were to identify the determinant factors for survival time of Human immunodeficiency virus (HIV) infected patients treated with highly active antiretroviral therapy (HAART) and to observe the HIV progression of HIV infected patients in Hawassa City Adare hospital, Ethiopia. Material and Methods: This was a retrospective cohort study of 330 patients who started ART between 2008 and 2014 at Hawassa City Adare Hospital. Data were extracted from paper based medical records database and the survival of patients was estimated by the Kaplan-Meier method. Predictors of mortality were identified by Cox proportional hazards model and the progression of the AIDS patients by Homogeneous Semi-Markov Stochastic model. Results: Survival of patients was significantly related with age, sex, Tuberculosis (TB) status, HIV disclosure, functional status, substance use, baseline World Health Organization (WHO) clinical stage, baseline weight and baseline cluster of differentiation 4 (CD4) count. Results of the Cox PH model revealed that; older, TB co-infected, substance user patients, and patients with lower baseline CD4 count and weight had significantly higher risk of death or shorter survival time than their counterparts. The results of Homogeneous Semi-Markov Stochastic model indicated that AIDS patients in the first state of the disease had the highest survival probability as compared to the patients in the second, third and fourth stage of the disease. Conclusion: To minimize deaths, more attention should be given during the early phases of treatment of HIV/AIDS patients on HAART.
Keywords: Cox proportional hazard model; HIV progression; Semi-Markov model
Amaç: Bu çalışmada, Etiyopya Hawassa Şehri Adare Hastanesi'nde yüksek düzeyde aktif antiretroviral tedavi (HAART) ile tedavi edilen, insan immün yetmezlik virüsü (HIV) enfeksiyonu ile enfekte hastaların sağkalım süreleri için belirleyici faktörlerin tanımlanması ve HIV ile enfekte hastalarda HIV progresyonunun gözlemlenmesi amaçlanmıştır. Gereç ve Yöntemler: Bu, Hawassa Şehri Adare Hastanesi'nde 2008-2014 yılları arasında antiretroviral tedavi başlanan 330 hastanın retrospektif bir kohort çalışmasıydı. Veriler, kağıt bazlı tıbbi kayıtlar veri tabanından çıkarılmış ve hastaların sağkalımları Kaplan-Meier metodu ile tahmin edilmiştir. Mortalitenin öngördürücüleri Cox orantılı risk modeli ile ve kazanılmış bağışıklık yetersizliği sendromu (AIDS) hastalarının progresyonu homojen semi-Markov stokastik modeli ile tanımlanmıştır. Bulgular: Hastaların sağkalımı yaş, cinsiyet, tüberküloz (TB) durumu, HIV durumu, işlevsel durum, madde kullanımı, Dünya Sağlık Örgütü'ne (DSÖ) göre başlangıçtaki klinik evre, başlangıç kilosu ve farklılaşma kümesi 4 (CD4) sayısı ile anlamlı olarak ilişkiliydi. Cox orantılı risk modelinin sonuçlarına göre; daha yaşlı, TB ile birlikte enfekte olmuş, madde kullanan hastalar ve daha düşük başlangıç CD4 sayısı ve ağırlığı olan hastalar benzerlerine göre daha yüksek ölüm oranlarına veya daha kısa sağkalım süresine sahiplerdi. Homojen semi-Markov stokastik modelin sonuçları, hastalığın birinci evresindeki AIDS hastalarının, hastalığın ikinci, üçüncü ve dördüncü evresindeki hastalara kıyasla en yüksek sağkalım olasılığına sahip olduğunu göstermiştir. Sonuç: Ölümleri en aza indirmek için, HAART tedavisi gören HIV/AIDS hastalarının tedavisinin erken evrelerinde daha fazla dikkat gösterilmelidir.
Anahtar Kelimeler: Cox oransal risk modeli; HIV progresyonu; Semi-Markov modeli
- AfDB, OECD, UNDP. African Economic Outlook: Ethiopia 2015. https://www.afdb.org/fileadmin/uploads/afdb/Documents/Publications/AEO2015_EN.pdf
- Disease Prevention and Control Department, AIDS in Ethiopia, 4th edn. Technical Document. Addis Ababa: Disease Prevention and Control Department, Ministry of Health, 2002.
- Poate D, Balogun P, Attawell K. UNAIDS Second Independent Evaluation 2002-2008: Country Visit to Ethiopia. Summary Report. (Oc-tober 8-23, 2008). https://data.unaids.org/pub/basedocument/2009/20091002_sie_final_report_en.pdf
- Johannessen A, Naman E, Ngowi BJ, Sandvik L, Matee MI, Aglen HE, et al. Predictors of mortality in HIV-1 infected patients starting antiretroviral therapy in a rural hospital in Tanzania. BMC Infect Dis. 2008;8:52. [Crossref] [PubMed] [PMC]
- Pathipvanich P, Ariyoshi K, Rojanawiwat A, Wongchoosie S, Yingseree P, Yoshiike K, et al. Survival benefit from non-highly active antiretroviral therapy in a resource-constrained setting. JAIDS Journal of Acquired Immune Deficiency Syndromes. 2003;3(2)2:157-60. [Crossref] [PubMed]
- Ferradini L, Jeannin A, Pinoges L, Izopet J, Odhiambo D, Mankhambo L, et al. Scaling up of highly active antiretroviral therapy in a rural district of Malawi: an effectiveness assessment. Lancet. 2006;367(9519):1335-42. [Crossref] [PubMed]
- Jiang X, Lu H, Zhang Y, Zhou Z, Ye H, Zhao Q, et al. A cross-sectional study of HIV and tuberculosis coinfection cases in mainland China. South Med J. 2008;101(9):914-7. [Crossref] [PubMed]
- López-Gatell H , Cole SR, Margolick JB, Witt MD, Martinson J, Phair JP, et al; Multicenter AIDS Cohort Study. Effect of tuberculosis on the survival of HIV-infected men in a country with low tuberculosis incidence. AIDS. 2008;22(14):1869-73. [Crossref] [PubMed] [PMC]
- Moh R, Danel C, Messou E, Ouassa T, Gabillara D, Anzian A, et al. Incidence and determinants of mortality and morbidity following early antiretroviral therapy initiation in HIV-infected adults in West Africa. AIDS. 2007;21(18):2483-91. [Crossref] [PubMed]
- Lawn SD, Little F, Bekker L, Kaplan R, Campbel E, Orrell C, et al. Changing mortality risk associated with CD4 cell response to antiretroviral therapy in South Africa. AIDS. 2009;23(3):335-42. [Crossref] [PubMed] [PMC]
- Adari JS. HIV/AIDS mortality differential across provinces in Kenya and through time. Texas Tech University. 2004. p.77. https://ttu-ir.tdl.org/bitstream/handle/2346/21407/31295019600963.pdf?sequence=1&isAllowed=y
- Sieleunou I, Souleymanou M, Schönenberger AM, Menten J, Boelaert M. Determinants of survival in AIDS patients on antiretroviral therapy in a rural center in the Far-North Province, Cameroon. Trop Med Int Health. 2009;14(1):36-43. [Crossref] [PubMed]
- Opportunistic Infections Project Team of the Collaboration of Observational HIV Epidemiological Research in Europe (COHERE) in Eu-roCoord, Young J, Psichogiou M, et al. CD4 cell count and the risk of AIDS or death in HIV-Infected adults on combination antiretroviral therapy with a suppressed viral load: a longitudinal cohort study from COHERE. PLoS Med. 2012;9(3):e1001194. [Crossref] [PubMed] [PMC]
- Kigozi BK, Sumba S, Mudyope P, Namuddu B, Kalyango J, Karamagi C, et al. The effect of AIDS defining conditions on immunological recovery among patients initiating antiretroviral therapy at Joint Clinical Research Centre, Uganda. AIDS Res Ther. 2009;6:17. [Crossref] [PubMed] [PMC]
- Reda AA, Biadgilign S, Deribew A, Gebre B, Deribe K. Predictors of change in CD4 lymphocyte count and weight among HIV infected patients on anti-retroviral treatment in Ethiopia: a retrospective longitudinal study. PLoS One. 2013;8(4):e58595. [Crossref] [PubMed] [PMC]
- Jerene D, Endale A, Hailu Y, Lindtjørn B. Predictors of early death in a cohort of Ethiopian patients treated with HAART. BMC Infectious Diseases. 2006;6:136. [Crossref] [PubMed] [PMC]
- Newman SC. Biostatistical Methods in Epidemiology. 1st ed. New York: John Wiley & Sons; 2001. p.408. [Crossref]
- Pyke R. Markov renewal processes with finitely many states. Ann Math Statist. 1961;32(4):1243-59. [Crossref]
- Jerene D, Næss A, Lindtjørn B. Antiretroviral therapy at a district hospital in Ethiopia prevents death and tuberculosis in a cohort of HIV patients. AIDS Research and Therapy. 2006;3:10. [Crossref] [PubMed] [PMC]
- Souto Melo AP, Guimarães MDC. [Factors associated with psychiatric treatment dropout in a mental health reference center, Belo Horizonte]. Rev Bras Psiquiatr. 2005;27(2):113-8. [Crossref] [PubMed]
- Goshu AT, Dessie ZG. Modelling progression of HIV/AIDS disease stages using semi-markov processes. Journal of Data Science. 2013;11:269-80.
- Di Biase G, D'Amico G, Di Girolamo A, Janssen J, Iacobelli S, Tinari N, et al. A stochastic model for the HIV/AIDS dynamic evolution. Mathematical problems in engineering. Hindawi. 2007. [Crossref]
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