Sukumaran Luxsena, Winston Alan, Post Frank A, Anderson Jane, Boffito Marta, Sachikonye Memory, Mallon Patrick W G, Waters Laura, Vera Jaime, Burns Fiona, Sabin Caroline A
Institute for Global Health, University College London.
National Institute for Health and Care Research (NIHR) Health Protection Research Unit (HPRU) in Blood-borne and Sexually Transmitted Infections at University College London.
AIDS. 2025 Oct 1;39(12):1784-1793. doi: 10.1097/QAD.0000000000004260. Epub 2025 Jun 4.
Despite increasing multimorbidity among people with HIV, its impact on health outcomes over time remains uncertain. We explored how distinct multimorbidity patterns affect a broad range of health outcomes over a 3-5-year period.
Principal component analysis (PCA) was used to identify multimorbidity patterns at baseline. Burden z -scores were calculated for each individual/pattern at baseline and a follow-up visit, and the differences in scores over time were examined. Participants completed health assessments including questionnaires [physical/mental health (SF-36)], depressive symptoms (CES-D and PHQ-9, falls, frailty and healthcare utilization), cognitive testing and pain mannequins tests. Multivariable regression models assessed associations between changes in morbidity burden z -scores and health outcomes.
Six multimorbidity patterns were identified in 1073 participants: " cardiovascular disease" (CVD) , " sexually transmitted infections" (STIs) , " metabolic" , " mental/joint" , " neurological" , and " cancer/other" . Subsequent analyses included 793 participants (median [interquartile range; IQR] age 53 [47-59] years; 86% male; 97% on ART) with follow up data. CVD and metabolic burden were associated with specialist appointments (CVD: β = 1.47; metabolic: β = 1.53, P < 0.01) and ED visits (CVD: β = 1.44; metabolic: β = 1.89, P < 0.01), mental/Joint and neurological burden with poorer physical and mental health, frailty and recurrent falls ( P < 0.01), and cancer/other burden with higher depressive scores (β = 3.28, P < 0.001), widespread pain (odds ratio, OR = 2.20, P < 0.001), and hospital visits (OR = 2.31, P < 0.001).
Distinct morbidity patterns differentially affected health outcomes and healthcare utilization over time, underscoring the need for targeted, integrated care to improve quality of life and address their complex needs.
尽管艾滋病毒感染者的多种疾病并存情况日益增多，但其对健康结果随时间推移的影响仍不确定。我们探讨了不同的多种疾病并存模式在3至5年期间如何影响广泛的健康结果。
采用主成分分析（PCA）在基线时识别多种疾病并存模式。计算每个个体/模式在基线和随访时的负担z分数，并检查分数随时间的差异。参与者完成了健康评估，包括问卷调查[身体/心理健康（SF-36）]、抑郁症状（CES-D和PHQ-9）、跌倒、虚弱和医疗保健利用情况、认知测试和疼痛模拟测试。多变量回归模型评估了发病率负担z分数变化与健康结果之间的关联。
在1073名参与者中识别出六种多种疾病并存模式：“心血管疾病”（CVD）、“性传播感染”（STIs）、“代谢性”、“精神/关节”、“神经学”和“癌症/其他”。后续分析纳入了793名有随访数据的参与者（年龄中位数[四分位间距；IQR]为53[47-59]岁；86%为男性；97%接受抗逆转录病毒治疗）。心血管疾病和代谢负担与专科门诊就诊相关（心血管疾病：β=1.47；代谢性：β=1.53，P<0.01）以及急诊就诊（心血管疾病：β=1.44；代谢性：β=1.89，P<0.01），精神/关节和神经负担与较差的身心健康、虚弱和反复跌倒相关（P<0.01），癌症/其他负担与较高的抑郁评分（β=3.28，P<0.001）、广泛疼痛（比值比，OR=2.20，P<0.001）和住院就诊（OR=2.31，P<0.001）相关。
不同的发病模式随时间推移对健康结果和医疗保健利用产生不同影响，强调需要有针对性的综合护理，以改善生活质量并满足他们的复杂需求。
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