Comparison of CHA2DS2-VASc-HS Score and Gensini Score to Predict Severity of Coronary Artery Disease
Journal Title: Journal of Clinical and Diagnostic Research - Year 2018, Vol 12, Issue 7
Abstract
Introduction: A plethora of risk assessment scores which identify the severity of Coronary Artery Disease (CAD) are available. However, most of them require results of coronary angiography or coronary computed tomography angiography. Aim: In this study, we assessed the accuracy of newly developed CHA2DS2-VASc-HS scoring system which does not require such sophisticated evaluations and compared it with Gensini score. Materials and Methods: The study was a single center, prospective, observational cohort study. The cohort of patients admitted to the Amrita School of Medicine, Kochi, Kerala, India for diagnostic angiography from November 2014 to October 2015 were observed for Gensini score and CHA2DS2-VASc-HS scores. Patients undergoing repeat angiography were excluded. The outcomes were classified into three groups as Normal, Mild CAD and Severe (Obstructive) CAD and the scores were compared. Statistical methods such an ANOVA, Spearman’s rank correlation and Mann-Whitney test were applied. Results: A total of 100 patients were studied whose mean age was 59.4±8.9 years. Among these patients, 19 patients (19%) had normal angiograms, 22 patients (22%) had mild CAD, and 59 (59%) patients had obstructive (severe) CAD. A significant increase in both the scores was observed with increase in severity of CAD. Mean Gensini score in the group with CHA2DS2-VASc-HS score <3 (n=44) was 2.34±4.13 (median-1, range 0-21), while the mean Gensini score in the group with CHA2DS2-VASc-HS score ≥3 (n=58) was 43.66±31.95 (median-33.8, range 0-153). There was a positive correlation between CHA2DS2-VASc-HS score and Gensini Score (correlation coefficient 0.813, p<0.001). Conclusion: This newly developed scoring system is an effective, convenient as well as rapid screening method, which can be used in hospital settings to predict severity of CAD.
Authors and Affiliations
Gautam Naik, Saritha Sekhar, Mukund Prabhu, Gurpreet Singh, Aniketh Vijay, Muthiah Subrahmanian, K U Natarajan
Keywords
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- EP ID EP523220
- DOI 10.7860/JCDR/2018/28509.11802
- Views 52
- Downloads 0
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