Spatiotemporal patterns and influencing factors of genotypic resistance testing utilization among people living with HIV: A 10-year retrospective analysis at a tertiary care hospital in Beijing, China (2014-2023)

艾滋病毒感染者基因型耐药性检测利用的时空模式及影响因素:中国北京一家三级医院10年回顾性分析(2014-2023年)

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Abstract

Prior research indicated low genotypic resistance testing (GRT) for human immunodeficiency virus (HIV) utilization in China due to partial cost coverage under national antiretroviral therapy policies, limited testing accessibility, and financial barriers. Temporal and spatial data on GRT trends were also scarce. We analyzed GRT patterns among 6,895 untreated individuals at a tertiary hospital using Joinpoint regression, multivariable logistic modeling, and spatial analysis (GeoDa/SatScan). GRT rates showed a significant two-phase upward trend, increasing from 5.36 % in 2014 to 74.17 % in 2023, with an average annual percentage change of 31.30 % (P < 0.001). Beijing residency (adjusted odds ratio [aOR] = 2.596, 95 % confidence interval [CI]: 2.307-2.921) and older age were associated with higher GRT uptake. Specifically, ages 35-44 years (aOR = 1.207, 95 % CI: 1.026-1.420), 45-54 years (aOR = 1.335, 95 % CI: 1.104-1.613), and ≥ 55 years (aOR = 1.424, 95 % CI: 1.126-1.802) had significantly higher odds of testing. Lower testing rates were observed in individuals with lower education attainment (high school or technical secondary: aOR = 0.827; junior high school: aOR = 0.835; primary school: aOR = 0.695), unknown sexually transmitted diseases (STDs) history (aOR = 0.415), and non-heterosexual transmission routes (homosexual: aOR = 0.834). Spatial analysis identified GRT clustering across Beijing until 2021, with two space-time clusters identified in 2019-2023 and 2018-2022. This study demonstrates substantial increase in GRT uptake achieving more balanced district-level distribution since 2021. Age, educational attainment, STDs history, and transmission route influence GRT utilization. Improving access, reducing costs, and implementing targeted interventions are critical for optimizing testing and guiding antiretroviral therapy decisions.

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