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Indian J Community Med. 2018 Jul-Sep;43(3):170-174. doi: 10.4103/ijcm.IJCM_255_17.

Ambiguity about Selection of Cardiovascular Risk Stratification Tools: Evidence from a North Indian Rural Population.

Author information

1
Department of Community Medicine, School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, India.
2
Department of Preventive and Social Medicine, RUHS College of Medical Sciences, Jaipur, Rajasthan, India.

Abstract

Background:

Several nonlaboratory based cardiovascular disease (CVD) risk scoring tools are available for resource-limited settings, but the performance of these tools remains to be established in Indian population. This study aimed to assess and compare the performance of the World Health Organization (WHO)/International Society for Hypertension (ISH) risk prediction chart and the Framingham Risk Score (FRS) calculator in an Indian setting.

Materials and Methods:

This cross-sectional study was carried out among 283 participants aged 30-74 years who attended screening camps in the rural area of Punjab from October to December 2015. Nonlaboratory-based WHO/ISH risk prediction chart for South-East Asia Region and FRS calculator was used to assess the 10-year risk of cardiovascular event. Chi-square test for trend and quadratic weighted kappa were used for analysis.

Results:

Of total participants, 67.1% were female. Mean age of the study participants was 52.1 (standard deviation ± 11.6) years. Using the WHO/ISH risk prediction chart, 11.3% and 4.9% of the participants were found to have high and very high risk, respectively, whereas, FRS calculator predicted high risk in 13.8% and very high risk in 12.0% for developing CVD in next 10 years. Agreement level between two risk prediction tools was good (67.8%).

Conclusion:

Although the good agreement was seen between WHO/ISH risk prediction chart and FRS calculator, the proportions of participants having a high and very high risk of CVD identified by these risk prediction tools are significantly different. In resource constraint setting like India, CVD risk prediction tools should be validated for local population by prospective cohort studies to ensure judicious use of resources.

KEYWORDS:

Cardiovascular diseases; health resources; primary care; risk

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