Harvard researchers develop new tools to predict risk of cardiovascular disease
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Harvard researchers develop new tools to predict risk of cardiovascular disease

January 30, 2017
Area(s) of Interest: Public Health 


A new study by researchers at Harvard T.H. Chan School of Public Health will help clinicians around the globe predict their patients’ 10-year risk of cardiovascular disease.

Cardiovascular diseases are the leading cause of death and disability worldwide, and more than three-quarters of cardiovascular disease-related deaths occur in low- and middle-income countries. But identifying those at high risk of having a future cardiovascular event can be difficult in many countries because there are no reliable risk charts, and because calculating risk typically relies on measurements of blood sugar and lipids—which, in resource-poor settings, can make the assessment too costly or impractical.

To address this problem, Harvard researchers developed risk charts for 182 nations to predict future risk of fatal and non-fatal cardiovascular events, including heart attack and stroke.

The complete set of risk charts and calculators are available online at www.globorisk.org.

“National and international guidelines recommend that physicians use risk prediction equations, usually in the form of risk charts, to predict which of their patients are at high risk for heart disease and stroke, and to suggest lifestyle modification or prescribe medication to lower their risk. These new risk charts, specifically calibrated for each country, remove major obstacles in applying risk-based strategies to prevent cardiovascular diseases,” said Goodarz Danaei, assistant professor of global health at Harvard Chan School and senior author of the paper.

The researchers developed two cardiovascular disease risk prediction models: one that uses lab-based blood measurements (a “laboratory-based model”), and one that can be used in the absence of bloodwork (an “office-based model”). To generate the models, researchers used data from eight long-term studies in the U.S. and recalibrated the models by using data on cardiovascular disease risk factor levels and rates for each target country.

The study found that, between 85 and 99 percent of the time, the office-based risk prediction model worked as well as the laboratory-based model in characterizing CVD risk. However, among diabetes patients, the office-based model noticeably underestimated the risk.

Click here to read the study, which was published last week in Lancet Diabetes and Endocrinology.

 

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