Journal of AIDS & Clinical Research

Predictors of Joint Modeling on Time to Mortality Progression with CD4 Cell Progression and Its Association with HIV/AIDS Patients Receiving ART in Mekelle General Hospital, Northern Ethiopia: A Retrospective Cohort Study

Abstract

Gebru Gebremeskel Gebrerufael* and Zeytu Gashaw Asfaw

Background of the study: The Acquired Immune Deficiency Syndrome (AIDS), which has caused the world's worst heartbreak and danger, is caused by the Human Immunodeficiency Virus (HIV), which is a virus. The purpose of this inquiry was to pinpoint the key joint predictor factors and their relationships, two of which were the progression of CD4 cells and the time to death for HIV/AIDS patients starting ART at Mekelle General Hospital (MGH) in Northern Ethiopia.

Methods: A longitudinal retrospective cohort follow-up study involving 216 HIV positive individuals was used to look into the progression of CD4 cells and the time to mortality in these patients. The primary joint predictor variables and their association with time-to-mortality for HIV/AIDS patients who started ART were found using a joint model analysis approach. In the general hospital's records, 216 HIV positive patients were selected systematically at random. The JM package and R 3.6.1 version procedure were used to examine the secondary data.

Results: The findings showed that there was a statistically significant negative relationship between the two response variables, CD4 cell count progression and time to mortality (α=-9.4; and p<0.0001^*). Being co-infected with (β=-0.125; and p<0.001^*), as well as the follow-up visit duration (β=-0.005 and p<0.001^*), had a statistically significant impact on the likelihood that the CD4 cells count would increase. Additionally, patients who were WHO stage-III or IV (AHR=1.7; and p<0.0384^*), or co-infected with TB (AHR=3.63; and p<0.002^*) had statistically been linked to a higher risk of mortality.

Conclusion: In order to simultaneously study the important effects of predictor factors on the change in CD4 cell count progression and the risk of patient mortality, the authors used that statistical joint model, which provides a flexible framework. The association parameter change of CD4 cell progression on the chances of mortality events was also evaluated by this combined model analysis.