Abstract
Sub-Saharan Africa remains the most affected region in the global AIDS epidemic. Côte d'Ivoire is one of the most affected countries by this epidemic. The collective search for deleterious determinants of the evolution of immunological markers (CD4 cells count) may help to optimize the therapeutic efficiency in this resource-limited country. We are interested in studying the antiretroviral response of efavirenz-based regimen (treatment of choice in first line) by the nonhierarchical-descendant model by taxonomy of CD4 cells count trajectories. From 87 CD4 cells count trajectories of symptomatic naive patients, classes of similar profiles grouped by the model have formed typical profiles of evolution as meta-trajectories. The analysis of these meta-trajectories was used to study the determinants of CD4 cells count evolution by classes of patients. Four classes have been determined for an optimal taxonomy with a partition score of 0.72: P1 (n=27), P2 (n=15), P3 (n=24), P4 (n=21). Our model showed a variation between groups of CD4 cells count trajectories linked to explanatory factors by highlighting the predictive role of certain characteristics on antiretroviral response in Côte d'Ivoire (CD4 cells count baseline [P<0.01], CD4 percentage baseline [P<0.05], adherence [P<0.05]). The multiple correspondence analysis revealed other characteristics that influence the immune response such as the presence of opportunistic infections, bloodless status and weight at the initiation of treatment. The factors influencing the profile of meta-trajectories of CD4 cells count during efavirenz-based antiretroviral regimen should be considered at the initiation of treatment to optimize performance in the therapeutic monitoring of patients in Abidjan. The model of biomedical indicators meta-trajectories provides a therapeutic decision support provided prior to capitalize sufficient expertise for a better interpretation.
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