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Non-AIDS complexity amongst patients living with HIV in Sydney: risk factors and health outcomes

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...

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Autores principales: Chan, Derek J., Furner, Virginia, Smith, Don E., Dronavalli, Mithilesh, Bopage, Rohan I., Post, Jeffrey J., Bhardwaj, Anjali K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5844086/
https://www.ncbi.nlm.nih.gov/pubmed/29519243
http://dx.doi.org/10.1186/s12981-018-0193-z
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author Chan, Derek J.
Furner, Virginia
Smith, Don E.
Dronavalli, Mithilesh
Bopage, Rohan I.
Post, Jeffrey J.
Bhardwaj, Anjali K.
author_facet Chan, Derek J.
Furner, Virginia
Smith, Don E.
Dronavalli, Mithilesh
Bopage, Rohan I.
Post, Jeffrey J.
Bhardwaj, Anjali K.
author_sort Chan, Derek J.
collection PubMed
description 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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spelling pubmed-58440862018-03-14 Non-AIDS complexity amongst patients living with HIV in Sydney: risk factors and health outcomes Chan, Derek J. Furner, Virginia Smith, Don E. Dronavalli, Mithilesh Bopage, Rohan I. Post, Jeffrey J. Bhardwaj, Anjali K. AIDS Res Ther Research 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. BioMed Central 2018-03-08 /pmc/articles/PMC5844086/ /pubmed/29519243 http://dx.doi.org/10.1186/s12981-018-0193-z Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Chan, Derek J.
Furner, Virginia
Smith, Don E.
Dronavalli, Mithilesh
Bopage, Rohan I.
Post, Jeffrey J.
Bhardwaj, Anjali K.
Non-AIDS complexity amongst patients living with HIV in Sydney: risk factors and health outcomes
title Non-AIDS complexity amongst patients living with HIV in Sydney: risk factors and health outcomes
title_full Non-AIDS complexity amongst patients living with HIV in Sydney: risk factors and health outcomes
title_fullStr Non-AIDS complexity amongst patients living with HIV in Sydney: risk factors and health outcomes
title_full_unstemmed Non-AIDS complexity amongst patients living with HIV in Sydney: risk factors and health outcomes
title_short Non-AIDS complexity amongst patients living with HIV in Sydney: risk factors and health outcomes
title_sort non-aids complexity amongst patients living with hiv in sydney: risk factors and health outcomes
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5844086/
https://www.ncbi.nlm.nih.gov/pubmed/29519243
http://dx.doi.org/10.1186/s12981-018-0193-z
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