Barbra E Backus1, A Jacob Six, Pieter A Doevendans, Johannes C Kelder, Ewout W Steyerberg, Yvonne Vergouwe. 1. From the *Department of Emergency Medicine, Medisch Centrum Haaglanden, The Hague, The Netherlands; †Department of Cardiology, Hofpoort hospital Woerden, Woerden, The Netherlands; ‡Department of Cardiology, University Medical Centre, Utrecht, The Netherlands; §Department of Research and Development, St Antonius Hospital, Nieuwegein, The Netherlands; and ¶Department of Public Health, Erasmus Medical Centre, Rotterdam, The Netherlands.
Abstract
OBJECTIVES: Risk stratification for chest pain patients at the emergency department is recommended in several guidelines. The history, ECG, age, risk factors, and troponin (HEART) score is based on medical literature and expert opinion to estimate the risk of a major adverse cardiac event. We aimed to assess the predictive effects of the 5 HEART components and to compare performances of the original HEART score and a model based on regression analysis. METHODS: We analyzed prospectively collected data from 2388 patients, of whom 407 (17%) had a major adverse cardiac event within 6 weeks (acute myocardial infarction, percutaneous coronary intervention, coronary artery bypass graft, significant stenosis with conservative treatment and death due to any cause). RESULTS: Univariate regression analysis showed the same ordering of predictive effects as used in the HEART score. Based on multivariable logistic regression analysis, an adjusted score showed slightly better calibration and discrimination (c statistic HEART, 0.83, HEART-adj, 0.85). In comparison to HEART, HEART-adj proved in a decision curve analysis clinically useful for decision thresholds over 25%. Nevertheless, the original HEART classified patients better than HEART-adj (net reclassification improvement = 14.1%). CONCLUSION: The previously chosen weights of the 5 elements of the HEART score are supported by multivariable statistical analyses, although some improvement in calibration and discrimination is possible by adapting the score. The gain in clinical usefulness is relatively small and supports the use of either the original or adjusted HEART score in daily practice.
OBJECTIVES: Risk stratification for chest painpatients at the emergency department is recommended in several guidelines. The history, ECG, age, risk factors, and troponin (HEART) score is based on medical literature and expert opinion to estimate the risk of a major adverse cardiac event. We aimed to assess the predictive effects of the 5 HEART components and to compare performances of the original HEART score and a model based on regression analysis. METHODS: We analyzed prospectively collected data from 2388 patients, of whom 407 (17%) had a major adverse cardiac event within 6 weeks (acute myocardial infarction, percutaneous coronary intervention, coronary artery bypass graft, significant stenosis with conservative treatment and death due to any cause). RESULTS: Univariate regression analysis showed the same ordering of predictive effects as used in the HEART score. Based on multivariable logistic regression analysis, an adjusted score showed slightly better calibration and discrimination (c statistic HEART, 0.83, HEART-adj, 0.85). In comparison to HEART, HEART-adj proved in a decision curve analysis clinically useful for decision thresholds over 25%. Nevertheless, the original HEART classified patients better than HEART-adj (net reclassification improvement = 14.1%). CONCLUSION: The previously chosen weights of the 5 elements of the HEART score are supported by multivariable statistical analyses, although some improvement in calibration and discrimination is possible by adapting the score. The gain in clinical usefulness is relatively small and supports the use of either the original or adjusted HEART score in daily practice.
Authors: Huilin Jiang; Yunmei Li; Junrong Mo; Xiaohui Chen; Min Li; Peiyi Lin; Kevin K C Hung; Timothy H Rainer; Colin A Graham Journal: BMC Cardiovasc Disord Date: 2018-05-16 Impact factor: 2.298
Authors: Min Ma; Kai-Yue Diao; Zhi-Gang Yang; Ye Zhu; Ying-Kun Guo; Meng-Xi Yang; Yi Zhang; Yong He Journal: Medicine (Baltimore) Date: 2018-07 Impact factor: 1.889