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Updated: Jun 26, 2026

An Affordable HIV-1 Drug Resistance Monitoring Method for Resource Limited Settings
Published on: March 30, 2014
Identifying risk factors for adverse drug reactions in HIV/AIDS patients using LASSO regression modeling
Shiqiong Huang1,2, Liang Gong3,4, Hui Qi1,5
1The Affiliated Changsha Hospital of Xiangya School of Medicine, Central South University, 311 Yingpan Road, Kaifu District, Changsha, Hunan, 410005, China.
Objective:
We perform a real-world study to investigate the incidence, clinical manifestations, suspected drugs, and associated risk factors of adverse drug reactions (ADRs) among Acquired Immunodeficiency Syndrome (AIDS) patients in the Chinese population.
Methods:
918 patients were enrolled in this retrospective study. All suspected ADRs were assessed for causality using the World Health Organization-Uppsala Monitoring Centre system. We employed least absolute shrinkage and selection operator (LASSO) regression to identify risk factors for ADRs in patients with HIV/AIDS.
Results:
210 of 918 patients experienced ADRs, with an incidence rate of 22.88%. Subsequently, standardized classification of ADRs was conducted using the Medical Dictionary for Regulatory Activities (MedDRA), revealing that blood and lymphatic system disorders were the most predominant manifestation, accounting for 5.77%. As to the type of drugs, Antibacterial (26.34%) and antiviral drugs (24.55%) were the most frequent causes for ADRs. Through the LASSO regression, the number of medications administered during hospitalization (odds ratio [OR] = 1.64, 95% confidence interval [CI]: 1.25-2.19) was identified as a significant influencing factor of ADRs in HIV patients.
Conclusion:
This study analyzed the specific manifestations of ADRs and their suspected drugs in hospitalized AIDS patients. More importantly, it revealed the potential correlation between the occurrence of ADRs and the number of medications administered during hospitalization in those patients. These findings provide a basis for clinical risk stratification management and offer reference data for optimizing treatment regimens.
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