Cd4 count progression of adult HIV patients under art follow up at mekelle general hospital, tigray region: A longitudinal data analysis approach

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Abstract

Background: The number of people receiving antiretroviral therapy (ART) in low-and middle-income countries continues to show encouraging growth, indicating that the global effort to scale up HIV treatment has exceeded 15 million people by the end of 2015. Methods: A retrospective cohort study, comprising of the quantitative method of data collection was conducted among randomly selected 210 adult ART users enrolled in the first 6 months of 2011 and followed up to mid-2016 which is a five year follow up. Data were analyzed using a linear mixed model to identify the determinant factors, which importantly incorporates the effect of factors over time. Results: Ninety-five (45%) were males and 115 (55%) were females. Composition of patients’ WHO clinical stage were; stage I (25 (11.8%)), stage II (30 (14.2%)), stage III (102 (48.8%)), and stage IV (52 (24.6%)). The mean CD4+ count at baseline was 218 cells. The progression of CD4+ count for males is lower than that of female over time (coef. =-0.0779, p-value=0.0062). There was a direct relationship between time in month and CD4+ count progression i.e., the CD4+ count progression of the adult HIV patients was increasing during the subsequent number of times measured or followed up under the ART clinic (coef. = 0.0435, p-value=0.0000). Patients with WHO stage II (coef. =-0.0982, p-value=0.0109), stage III (coef. =-0.0884, p-value = 0.0010) and stage IV (coef. = 0.0859, p-value = 0.0095) had lower CD4+ count than the reference category WHO clinical stage I over time. Conclusion: In conclusion, we found that the WHO clinical stage, Time, Weight, Gender and the Interaction effects of Weight with Time were significantly associated with the progression of CD4+ counts over time.

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Meles, H. G., Temesgen, H., & Alemayehu, M. (2019). Cd4 count progression of adult HIV patients under art follow up at mekelle general hospital, tigray region: A longitudinal data analysis approach. Epidemiology Biostatistics and Public Health, 16(4). https://doi.org/10.2427/13234

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