Department of Biostatistics

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    JOINT MODELING OF TIME TO DEVELOP TUBERCULOSIS AND CHANGE IN CD4 COUNT AMONG HIV PATIENTS UNDER ART IN MEKELLE, ETHIOPIA, 2024
    (Mekelle University, 2025-06-28) TEKLEBRHAN KINFE
    Background: In patients with HIV, tuberculosis remains the leading cause of mortality and morbidity. Little is known about the predictors and the median time to develop tuberculosis while considering for the effect of the variation of longitudinal CD4 cell count. Objective: To investigate the time to develop tuberculosis accounting for longitudinal CD4 cell count change and its predictors among HIV patients who are under ART follow-up at Mekelle General Hospital and Ayder Comprehensive Specialized Hospital, Mekelle, Ethiopia, 2024. Methodology: A facility-based retrospective follow-up study was conducted among 449 adult PLHIV under ART follow-up from March 2018 to May 2024. The study participant were selected via a simple random sampling. The secondary data were collected from the patients’ medical records via Kobocollect version 2021.2.4 and exported to STATA version 17.0. The final model was a joint random intercept Cox-proportional hazard model. A model with the lowest Akaike information criterion and Bayesian information criterion was selected. Results: The incidence density of TB disease was 6.77 cases/100 person-years with a restricted mean survival time of 60 months. The joint analysis provided an association parameter alpha with AHR=0.854; 95% CI(0.8-0.91), indicating that for a unit increase in the average √CD4 cell count , the hazard of TB infection decreased by 14.6%, keeping other variables constant. The study also revealed that advanced WHO clinical stage (AHR = 1.024, 95% CI: 1.017–1.033), sex (AHR= 1.62, 95% CI: 1.09,2.4), CPT intake (AHR= 0.55, 95% CI: 0.35,0.89), and adherence (AHR= 0.38, 95% CI: 0.28,0.52) were significantly associated with the time to develop tuberculosis. The random intercept model indicated that greater variation in CD4 counts at baseline contributed strongly to the hazard of tuberculosis. Conclusion and Recommendation: This research highlights that PLHIV with a decreasing trajectory of CD4 count, advanced WHO clinical stage, female sex, history of CPT intake, and poor adherence have a higher risk of tuberculosis. On the basis of these findings, it is strongly recommended that the government and relevant health actors working on TB/HIV should intensify activities that improve patient adherence and a regular CD4 cell measurement.
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    Joint Modeling of Longitudinal Blood Pressure and Time to Complications Among Hypertensive Patients: A Retrospective Cohort Study in Mekelle, Ethiopia, 2018-2024
    (Mekelle University, 2025-06-28) MISHO MLAW
    Introduction: Hypertension is one of the 21st century emerging major public health problem, which is a strong risk factor for myocardial infraction, heart failure, ischemic or hemorrhagic stroke, chronic kidney disease, and eye disorder. Despite its significance, limited studies have investigated the association between longitudinal blood pressure measurements and the time to development of complications among hypertensive patients. Objectives: To determine the predictors, association between longitudinal blood pressure measurements and time to develop complications among hypertensive patients in ACSH and Mekelle General Hospital, Tigray, Ethiopia, 2018-2024. Methodology: A retrospective cohort study among 403 adult hypertensive patients with no complications from the beginning of follow up in Ayder Comprehensive Specialized Referral Hospital and Mekelle General Hospital from January 2018 to March 2024 was included. Data from patient’s medical record was collected using Kobo toolbox and exported to Stata version 17 and R 4.4.3 for data management and analysis. A bivariate mixed-effects model, Cox proportional hazards model, and a multivariate joint model linking longitudinal and survival sub-models through shared random effects were fitted. The final interpretation was done by hazard ratio. Result: A multivariate joint modeling analysis was the best fitted model based on the minimum Akaike Information Criterion value with an estimated value of the association parameters of 10.4 (p < 0.001) and 4.9 (p = 0.040), supporting the association between systolic and diastolic blood pressure with time to event was statistically significant. The multivariate joint modeling analysis showed that patients with family history of cardiovascular diseases (Hazard Ratio = 4.31), patient with Diabetes mellitus comorbidity (Hazard Ratio = 3.86), patient who take multiple treatment regimens have higher chance of developing hypertension related complications. Both Systolic and Diastolic blood pressure measurements were found to be critical predictors of hypertension complications. Conclusion and Recommendation - This study highlights the importance of effective blood pressure management and the need for targeted interventions that account for family history, clinical comorbidities, and treatment regimens to reduce the risk of complications in hypertensive patients.