| dc.description.abstract | Despite significant advancements in antiretroviral therapy (ART), HIV/AIDS remains a critical health challenge in Meru County, Kenya, particularly concerning the high mortality rates among people living with HIV (PLHIV). The persistent mortality underscores the need for a deeper understanding of the factors contributing to this trend. The study’s general objective was to conduct a survival modeling of mortality in adult HIV/AIDS patients following antiretroviral therapy: A case of Meru Teaching and Referral Hospital. The specific objectives of the study aimed to investigate the determinants linked to increased mortality, fit a survival model for predicting mortality and evaluate survival differences among adult HIV/AIDS patients under ART at Meru Teaching and Referral Hospital (MTRH). A retrospective cohort study design was adopted, utilizing secondary data from MTRH for all HIV-positive adults who received ART between January 1, 2018, and December 31, 2023. The target population comprised patients whose complete medical records were available for analysis. The data collected included demographic, socioeconomic, and clinical variables, with mortality as the event of interest. Data were de-identified to ensure patient privacy and were entered into an Excel spreadsheet for cleaning and analysis using R statistical software. Quantitative analysis was conducted using the 'survival' package in R. Descriptive statistics were used to characterize the study population, while logistic regression and Cox Proportional Hazards regression models were employed to identify determinants linked to increased mortality and to fit a survival model for predicting mortality, respectively. Additionally, the Log-rank test was used to evaluate survival differences among PLHIV across different treatment groups under ART. The logistic regression analysis revealed that gender, age, smoking status, employment status, education level, CD4 cell count, and TB screening were critical covariates associated with mortality among PLHIV. Specifically, Male patients had a 25% higher odds of mortality occurring compared to female patients. Age was conversely related to mortality with each additional year of age, the odds of mortality increased by 2%. The Cox PH model further confirmed that gender and age were significant predictors of mortality, while the other factors did not significantly impact survival in this cohort. The findings found that being male was associated with a 72% higher hazard of mortality than females (exp(coef) = 1.718). Age was conversely related to mortality risk, with each additional year increasing the hazard by 1.5% (coefficient = 1.015). However, smoking status and employment were not significantly associated with mortality. The Log-rank test revealed a significant difference in survival rates between male and female participants (χ² = 4.1, df = 1, p = .04), with females exhibiting better survival outcomes. However, no significant survival differences were observed based on age, smoking status, or marital status. The study concluded that gender, age, and other covariates play essential roles in determining mortality among PLHIV under ART. The findings highlight the need for gender-sensitive healthcare interventions, age-appropriate care strategies, and comprehensive socioeconomic support to improve survival outcomes. The study recommends further research to explore the specific challenges faced by male PLHIV. Additionally, future research should investigate the effects of various aspects of socioeconomic status such as income level, job stability, and access to financial assistance to gain a deeper understanding of how socioeconomic factors influence survival outcomes among PLHIV | en_US |
