VALIDATION OF THE POOLED COHORT RISK SCORE AND THE THAI CV RISK SCORE FOR ATHEROSCLEROSIS-CARDIOVASCULAR DISEASE (ASCVD) RISK PREDICTION AT WARINCHAMRAB HOSPITAL
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Creator Peerawat Jinatongthai
Title VALIDATION OF THE POOLED COHORT RISK SCORE AND THE THAI CV RISK SCORE FOR ATHEROSCLEROSIS-CARDIOVASCULAR DISEASE (ASCVD) RISK PREDICTION AT WARINCHAMRAB HOSPITAL
Contributor Wannisa Dongtai, Boonthida Aonsuebsai, Possawat Towongsricharoen, Thanatcha Songmuang, Sawaeng Watcharathanakij, Surakit Nathisuwan
Publisher Faculty of pharmacy, Silpakorn University
Publication Year 2564
Journal Title Thai Bulletin of Pharmaceutical Sciences
Journal Vol. 16
Journal No. 2(July-December)2021
Page no. 71-81
Keyword risk score, atherosclerotic cardiovascular disease, Pooled cohort risk score, Thai CV risk score, Thailand
URL Website https://li01.tci-thaijo.org/index.php/TBPS
ISSN 2586-8659
Abstract Cardiovascular disease is a major health problem in Thailand. Predicting the risk of cardiovascular disease developing in patients can help to guide the formulation of treatment plans. This study aimed to validate the use of the Pooled Cohort risk score and the Thai CV risk score, in patients at Warinchamrap hospital. We conducted a retrospective cohort study on patients aged 40-70 years for whom electronic medical records are held at Warinchamrap hospital, covering the years 1997 to 2017. The discrimination and calibration of the risk scores were assessed using c-index and Hosmer-Lemeshow statistics, respectively. The results of this study found that 100% of the 1,171 patients investigated were predicted to be at low risk when assessed by the Pooled Cohort Risk score (risk scores <7.5%) and 93.65% at low risk when assessed by the Thai CV risk score (risk score <10%). Both risk scores showed fair discrimination (0.613 [95% CI, 0.562-0.665] and 0.614 [95% CI, 0.564-0.663], respectively) and good calibration (X2=9.334 [p-value 0.315] and 12.973 [p-value 0.113], respectively). In conclusion, the Pooled Cohort risk score and Thai CV risk score can be used to predict ASCVD risk in patients.
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