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Updated: Feb 13, 2026

Measurement of In Vitro Integration Activity of HIV-1 Preintegration Complexes
Published on: February 22, 2017
Non-AIDS complexity amongst patients living with HIV in Sydney: risk factors and health outcomes
Derek J Chan1,2, Virginia Furner1, Don E Smith3,4
1Albion Centre, South Eastern Sydney Local Health District, Sydney, NSW, 2010, Australia.
Objective:
To assess the prevalence of non-AIDS co-morbidities (NACs) and predictors of adverse health outcomes amongst people living with HIV in order to identify health needs and potential gaps in patient management.
Design:
Retrospective, non-consecutive medical record audit of patients attending a publicly funded HIV clinic in metropolitan Sydney analysed for predictors of adverse health outcomes. We developed a scoring system based on the validated Charlson score method for NACs, mental health and social issues and confounders were selected using directed acyclic graph theory under the principles of causal inference.
Results:
211 patient files were audited non-consecutively over 6 weeks. 89.5% were male; 41.8% culturally and linguistically diverse and 4.1% were of Aboriginal/Torres Strait Islander origin. Half of patients had no general practitioner and 25% were ineligible for Medicare subsidised care. The most common NACs were: cardiovascular disease (25%), hepatic disease (21%), and endocrinopathies (20%). One-third of patients had clinical anxiety, one-third major depression and almost half of patients had a lifetime history of tobacco smoking. Five predictors of poor health outcomes were identified: (1) co-morbidity score was associated with hospitalisation (odds ratio, OR 1.58; 95% CI 1.01-2.46; p = 0.044); (2) mental health score was associated with hospitalisation (OR 1.79; 95% CI 1.22-2.62; p = 0.003) and poor adherence to ART (OR 2.34; 95% CI 1.52-3.59; p = 0.001); (3) social issues score was associated with genotypic resistance (OR 2.61; 95% CI 1.48-4.59; p = 0.001), co-morbidity score (OR 1.69; 95% CI 1.24-2.3; p = 0.001) and hospitalisation (OR 1.72; 95% CI 1.1-2.7; p = 0.018); (4) body mass index < 20 was associated with genotypic resistance (OR 6.25; 95% CI 1.49-26.24; p = 0.012); and (5) Medicare eligibility was associated with co-morbidity score (OR 2.21; 95% CI 1.24-3.95; p = 0.007).
Conclusion:
Most HIV patients are healthy due to effective antiretroviral therapy; however, NACs and social/mental health issues are adding to patient complexity. The current findings underpin the need for multidisciplinary management beyond routine viral load and CD4 count monitoring.
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