A model for predicting high BMI of people living with HIV after receiving antiretroviral therapy.

Ther Adv Chronic Dis

Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, No. 1838, Guangzhou Avenue North, Guangzhou 510515, Guangdong, China.

Published: June 2022

Objective: The objective of this study was to evaluate the characteristics of high body mass index (BMI) and normal weight people living with HIV after antiretroviral therapy (ART) and establish a model.

Methods: A total of 290 people living with HIV after 1 year of ART treatment were enrolled and divided into two groups based on whether their BMI index was <24 or ⩾24 at week 48. The demographic, clinical data were collected and analyzed. Multivariable logistic regression analysis was performed. A model was established and use to predict the occurrence of certain diseases.

Results: A total of 290 people living with HIV were included in this study; 200 had a normal BMI (BMI < 24) and 90 were high BMI (BMI ⩾ 24) after 1-year ART. Their baseline characteristics were significantly different in relation to age ( = 0.007), sex distribution ( = 0.040), ART regimen ( = 0.040), alanine aminotransferase levels ( < 0.001), and three major serum lipid levels: triglycerides ( < 0.001), cholesterol ( = 0.011), and low-density lipoprotein ( = 0.005). A multivariate logistic regression analysis resulted in the development of a model for the diagnosis of high BMI and hyperlipidemia. The model score is an independent risk factor for hyperlipidemia (odds ratio = 2.674,  = 0.001) and high BMI ( < 0.001). The model score is significantly correlated with the controlled attenuation parameter (CAP) value ( = 0.230,  < 0.001) and can be used to divide the severity of liver steatosis based on CAP value.

Conclusions: This study demonstrated a easy-to-use model to detect high BMI, hyperlipidemia, and liver steatosis in people living with HIV without risk factors for BMI changing at baseline after 1 year of ART treatment.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9218435PMC
http://dx.doi.org/10.1177/20406223221102750DOI Listing

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