Post-ART Immune Reconstitution Prediction Model in AIDS Patients with
CD4 as the Grouping Variable
Abstract
Objective To explore if CD4 can be used as an index to guide the ART
compliance and predict the feasibility of post-ART immune
reconstitution. Methods The data of outpatients with AIDS visiting the
research unit from August 2009 to April 2021 were used. The patients
were divided according to the grouping variable (CD4 in the last 1-6
consecutive times ≥ 500 cells/μL) into good immune reconstitution and
poor immune reconstitution groups. Based on the baseline CD4 value, the
patients were classified into 6 types. The optimal grouping variable was
used to establish the post-ART immune reconstitution prediction models,
and inference rules were generated. Results A total of 7,872 pieces of
valid data were obtained, including 4,834 in the incomplete immune
reconstitution group (CD4 ≥ 500 cells/μL or < 500 cells/μL).
Taking CD4 in the last 6 consecutive times ≥ 500 cells/μL as the optimal
grouping variable, 6 immune reconstitution prediction models were
established, with accuracies ranging within 89.4-93.29%, and 29
inference rules were generated. Good immune reconstitution rules were
more complex than poor immune reconstitution rules and had more
additional conditions; the confidence was high. It was found to usually
take 42 months of adherence to ART treatment to enter a good immune
reconstitution state. Conclusion The model established based on the
optimal grouping variable of CD4 in the last 6 consecutive times ≥ 500
cells/μL and the corresponding inference rules can effectively guide
ART, assess the post-ART immune reconstitution status and lower the
medical burden of ART.