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Post-ART Immune Reconstitution Prediction Model in AIDS Patients with CD4 as the Grouping Variable
  • Min Li,
  • Qunwei Wang,
  • yinzhong shen
Min Li

Corresponding Author:[email protected]

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Qunwei Wang
Nanjing University of Aeronautics and Astronautics
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yinzhong shen
Shanghai Public Health Clinical Center
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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.