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Comparison of the performance of cardiovascular risk prediction tools in rural India: the Rishi Valley Prospective Cohort Study.
Birhanu, Mulugeta Molla; Zengin, Ayse; Evans, Roger G; Joshi, Rohina; Kalyanram, Kartik; Kartik, Kamakshi; Danaei, Goodarz; Barr, Elizabeth; Riddell, Michaela A; Suresh, Oduru; Srikanth, Velandai K; Arabshahi, Simin; Thomas, Nihal; Thrift, Amanda G.
Afiliação
  • Birhanu MM; Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Level 5, Block E, Monash Medical Centre, 246 Clayton Road, Melbourne, Victoria 3168, Australia.
  • Zengin A; Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Level 5, Block E, Monash Medical Centre, 246 Clayton Road, Melbourne, Victoria 3168, Australia.
  • Evans RG; Cardiovascular Disease Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Melbourne, Victoria, Australia.
  • Joshi R; Pre-clinical Critical Care Unit, Florey Institute of Neuroscience and Mental Health, University of Melbourne, Melbourne, Victoria, Australia.
  • Kalyanram K; Faculty of Medicine, School of Population Health, University of New South Wales, Sydney, Australia.
  • Kartik K; George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia.
  • Danaei G; George Institute for Global Health, New Delhi, India.
  • Barr E; Rishi Valley Rural Health Centre, Madanapalle, Chittoor District, Andhra Pradesh, India.
  • Riddell MA; Rishi Valley Rural Health Centre, Madanapalle, Chittoor District, Andhra Pradesh, India.
  • Suresh O; Department of Global Health and Population and Epidemiology, Harvard University T H Chan School of Public Health, Boston, MA, USA.
  • Srikanth VK; Menzies School of Health Research, Charles Darwin University, Darwin, Northern Territory, Australia.
  • Arabshahi S; Clinical Diabetes and Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
  • Thomas N; Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Level 5, Block E, Monash Medical Centre, 246 Clayton Road, Melbourne, Victoria 3168, Australia.
  • Thrift AG; Department of Medicine, School of Clinical Sciences at Monash Health, Monash University, Level 5, Block E, Monash Medical Centre, 246 Clayton Road, Melbourne, Victoria 3168, Australia.
Eur J Prev Cardiol ; 31(6): 723-731, 2024 Apr 18.
Article em En | MEDLINE | ID: mdl-38149975
ABSTRACT

AIMS:

We compared the performance of cardiovascular risk prediction tools in rural India. METHODS AND

RESULTS:

We applied the World Health Organization Risk Score (WHO-RS) tools, Australian Risk Score (ARS), and Global risk (Globorisk) prediction tools to participants aged 40-74 years, without prior cardiovascular disease, in the Rishi Valley Prospective Cohort Study, Andhra Pradesh, India. Cardiovascular events during the 5-year follow-up period were identified by verbal autopsy (fatal events) or self-report (non-fatal events). The predictive performance of each tool was assessed by discrimination and calibration. Sensitivity and specificity of each tool for identifying high-risk individuals were assessed using a risk score cut-off of 10% alone or this 10% cut-off plus clinical risk criteria of diabetes in those aged >60 years, high blood pressure, or high cholesterol. Among 2333 participants (10 731 person-years of follow-up), 102 participants developed a cardiovascular event. The 5-year observed risk was 4.4% (95% confidence interval 3.6-5.3). The WHO-RS tools underestimated cardiovascular risk but the ARS overestimated risk, particularly in men. Both the laboratory-based (C-statistic 0.68 and χ2 26.5, P = 0.003) and non-laboratory-based (C-statistic 0.69 and χ2 20.29, P = 0.003) Globorisk tools showed relatively good discrimination and agreement. Addition of clinical criteria to a 10% risk score cut-off improved the diagnostic accuracy of all tools.

CONCLUSION:

Cardiovascular risk prediction tools performed disparately in a setting of disadvantage in rural India, with the Globorisk performing best. Addition of clinical criteria to a 10% risk score cut-off aids assessment of risk of a cardiovascular event in rural India. LAY

SUMMARY:

In a cohort of people without prior cardiovascular disease, tools used to predict the risk of cardiovascular events varied widely in their ability to accurately predict who would develop a cardiovascular event.The Globorisk, and to a lesser extent the ARS, tools could be appropriate for this setting in rural India.Adding clinical criteria, such as sustained high blood pressure, to a cut-off of 10% risk of a cardiovascular event within 5 years could improve identification of individuals who should be monitored closely and provided with appropriate preventive medications.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doenças Cardiovasculares / Hipertensão Limite: Humans / Male País como assunto: Oceania Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doenças Cardiovasculares / Hipertensão Limite: Humans / Male País como assunto: Oceania Idioma: En Ano de publicação: 2024 Tipo de documento: Article