Factors associated with readmission risk in patients with HIV stratified by BMI: a hospital-based retrospective study

Objective: To assess risk factors for repeated hospitalization in patients with human immunodeficiency virus (HIV) stratified by BMI and to provide evidence for clinical diagnosis, treatment, and nursing. Methods: : Patients admitted to our hospital from January 2020 to June 2020 were included in the study group, and patients with repeat hospitalizations (≥ 2) during 2 years of follow-up were included in the observation group; a 1:1 case-control group was selected according to the general data such as age and sex and stratified by baseline body mass index（BMI）(< 18.5 kg/m 2 , ≥ 18.5 &＜25kg/m 2 ). Demographic and clinical data were collected and analyzed. Binary logistic regression was used to analyze risk factors for repeat hospitalization in patients with AIDS with different baseline BMIs. Results: : This study included 311 individuals with HIV, of whom 80 had a BMI < 18.5 kg/m 2 (low body weight)and 231 had a BMI ≥ 18.5&＜28 kg/m 2 (normal body weight). The readmission rate of those with low body weight was higher than those normal body weight ( p = 0.025). In patients with HIV with a baseline BMI < 18.5 kg/m 2 , unemployment (versus employment) and lowest CD4+ T cell count were independent risk factors for readmission. The receive operating characteristic (ROC) curve constructed using these two variables performed better than other variables in predicting readmission in the lower BMI group. In contrast, in patients with HIV with a BMI ≥ 18.5&＜28 kg/m 2 , unemployment (versus employment) and time since diagnosis > 5 years (versus 0–1 years) were risk factors, whereas marital status of widowed or divorced was a protective factor (versus married). Furthermore, the ROC curve including these three variables performed better than other variables in predicting readmission in the higher BMI group. Conclusions: : Risk factors for repeat hospitalization varied among patients with AIDS patients with different baseline BMIs. For individuals with HIV, the present model can be effectively and efficiently used to predict the occurrence of readmission based on BMI.