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Development and Use of Prediction Models for Classification of Cardiovascular Risk of Remote Indigenous Australians - 28/02/20

Doi : 10.1016/j.hlc.2019.02.005 
An Tran-Duy, PhD a, ⁎ , Robyn McDermott, PhD b, c, Josh Knight, PhD a, Xinyang Hua, PhD a, Elizabeth L.M. Barr, PhD d, e, Kerry Arabena, PhD f, Andrew Palmer, MD, PhD a, g, Philip M. Clarke, PhD a, h
a Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Vic, Australia 
b Centre for Chronic Disease Prevention, James Cook University, Cairns, Qld, Australia 
c School of Health Sciences, University of South Australia, Adelaide, SA, Australia 
d Menzies School of Health Research, Darwin, NT, Australia 
e Baker Heart and Diabetes Institute, Melbourne, Vic, Australia 
f Centre for Health Equity, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Vic, Australia 
g Menzies Institute for Medical Research, University of Tasmania, Hobart, Tas, Australia 
h Health Economics Research Centre, Nuffield Department of Population Health, University of Oxford, Oxford, UK 

⁎Corresponding author at: Centre for Health Policy, School of Population and Global Health The University of Melbourne, Level 4, 207 Bouverie Street, Carlton, Victoria 3053, Australia. Tel.: +61 3 90356387; Fax: +61 3 9348 1174.Centre for Health PolicySchool of Population and Global Health The University of MelbourneLevel 4, 207 Bouverie StreetCarltonVictoria3053Australia

Riassunto

Background

Cardiovascular disease (CVD) is the leading cause of death for Indigenous Australians. There is widespread belief that current tools have deficiencies for assessing CVD risk in this high-risk population. We sought to develop a 5-year CVD risk score using a wide range of known risk factors to further improve CVD risk prediction in this population.

Methods

We used clinical and demographic information on Indigenous people aged between 30 and 74 years without a history of CVD events who participated in the Well Person’s Health Check (WPHC), a community-based survey. Baseline assessments were conducted between 1998 and 2000, and data were linked to administrative hospitalisation and death records for identification of CVD events. We used Cox proportional hazard models to estimate the 5-year CVD risk, and the Harrell’s c-statistic and the modified Hosmer-Lemeshow (mH-L) χ2 statistic to assess the model discrimination and calibration, respectively.

Results

The study sample consisted of 1,583 individuals (48.1% male; mean age 45.0 year). The risk score consisted of sex, age, systolic blood pressure, diabetes mellitus, waist circumference, triglycerides, and albumin creatinine ratio. The bias-corrected c-statistic was 0.72 and the bias-corrected mH-L χ2 statistic was 12.01 (p-value, 0.212), indicating good discrimination and calibration, respectively. Using our risk score, the CVD risk of the Indigenous Australians could be stratified to a greater degree compared to a recalibrated Framingham risk score.

Conclusions

A seven-factor risk score could satisfactorily stratify 5-year risk of CVD in an Indigenous Australian cohort. These findings inform future research targeting CVD risk in Indigenous Australians.

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Keywords : Aboriginal, Torres Strait Islanders, Prediction model, Risk score, Cardiovascular disease, Coronary heart disease


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© 2019  The Authors. Pubblicato da Elsevier Masson SAS. Tutti i diritti riservati.
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Vol 29 - N° 3

P. 374-383 - marzo 2020 Ritorno al numero
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