Non-AIDS complexity amongst patients living with HIV in Sydney: risk factors and health outcomes
Tóm tắt
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. 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. 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). 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.
Tài liệu tham khảo
Weber R, Ruppik M, Rickenbach M, Spoerri A, Furrer H, Battegay M, et al. Decreasing mortality and changing patterns of causes of death in the Swiss HIV Cohort Study. HIV Med. 2013;14:195–207.
Phillips AN, Neaton J, Lundgren JD. The role of HIV in serious diseases other than AIDS. AIDS. 2008;22:2409–18.
Friis-Moller N, Weber R, Reiss P, Thiébaut R, Kirk O, d’Arminio Monforte A, et al. Cardiovascular disease risk factors in HIV patients—association with antiretroviral therapy. Results from the DAD study. AIDS. 2003;17:1179–93.
Shrier I, Platt RW. Reducing bias through directed acyclic graphs. BMC Med Res Methodol. 2008;8:70.
Pearl J. Causal inference from indirect experiments. Artif Intell Med. 1995;7:561–82.
Austin SR, Wong YN, Uzzo RG, Beck JR, Egleston BL. Why summary comorbidity measures such as the Charlson comorbidity index and Elixhauser score work. Med Care. 2015;53(9):e65–72.
Petoumenos K, Huang R, Hoy J, Bloch M, Templeton D, Baker D et al. APPLES—the australian positive & peers longevity evaluation study. In: Conference on retroviruses and opportunistic infections. 2017, Seattle.
Wieland D, Hirth V. Comprehensive geriatric assessment. Cancer Control. 2003;10(6):454–62.
Guaraldi G, Brothers TD, Zona S, Stentarelli C, Carli F, Malagoli A, et al. A frailty index predicts survival and incident multimorbidity independent of markers of HIV disease severity. AIDS. 2015;29(13):1633–41. https://doi.org/10.1097/qad.0000000000000753.
Rockwood K, Song X, MacKnight C, Bergman H, Hogan DB, McDowell I, Mitnitski A. A global clinical measure of fitness and frailty in elderly people. CMAJ. 2005;173(5):489–95.
Suttorp MM, Siegerink B, Jager KJ, Zoccali C, Friedo W, Dekker FW. Graphical presentation of confounding in directed acyclic graphs. Nephrol Dial Transplant. 2015;30(9):1418–23. https://doi.org/10.1093/ndt/gfu325.
Thornley S, Marshall RJ, Wells S, Jackson R. Using directed acyclic graphs for investigating causal paths for cardiovascular disease. J Biomet Biostat. 2013;4:182. https://doi.org/10.4172/2155-6180.1000182.
Pizzi C, De Stavola BL, Pearce N, Lazzarato F, Ghiotti P, Merletti F, et al. Selection bias and patterns of confounding in cohort studies: the case of the NINFEA web-based birth cohort. J Epidemiol Community Health. 2012;66(11):976–81. https://doi.org/10.1136/jech-2011-200065.
Thelaus A, Pettersson T, Gordon M, Krupic F, Sköldenberg O. A prospective observational cohort study on orthopaedic and anaesthetic registrars performing femoral nerve block on patients with an acute hip fracture. Surg Res Pract. 2016. https://doi.org/10.1155/2016/7512360.
Lau B, Gange, Stephen J, Moore R. Risk of non-AIDS-related mortality may exceed risk of AIDS-related mortality among individuals enrolling into care with CD4 + counts greater than 200 cells/mm3. J Acquir Immune Defic Syndr. 2007;44(2):179–87.