Repeated Measure Analysis for the CD4<sup>+</sup> Cell Counts of HIV-Positive Patients Initiated to ART: A Case Study at Ambo Hospital

Abstract

Introduction: HIV is a virus that causes Acquired Immunodeficiency Syndrome (AIDS) by reducing a person's ability to fight the infection. It attacks an immune cell called the CD4 cell which is responsible for the body's immune response to infectious agents. Now a days anti retro viral therapy treatment is avail to elongate the life of patients. The treatment is given for patients to increase the CD4 counts of patients to keep the ability of body preventing the disease. Objectives: This study was aimed to identify the potential associated risk factors with CD4 counts of patients under ART treatment at public hospital in Ethiopia. The other was to fit linear mixed model by handling missing value of the data during follow up time. Method: To see the structure of the data, exploratory data analysis was conducted. Of the familiar variance structures, unstructured variance covariance is selected to be best and to fit the data under study, step-by-step procedure was passed to obtain best model. Results: The descriptive statistics directed that the progressive change in CD4 counts of females seems better than that of males. On the other hand, the output of the fitted model indicated that covariates significant with 5% level of significance is that baseline CD4, time, weight and interaction of Sex, baseline CD4 with time. Allowing the significance level to increase to 25% increases most covariates to be significant that help patients in a better awareness. Conclusion: With this result, full linear mixed with random intercept and slop is found to best model. There was high variability within patients over time and between patients and the interaction of time with covariates was also significant. Generally, the data was fitted by handling the missing value using multiple imputation technique.