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Greek acute coronary syndrome score for the prediction of in-hospital and 30-day mortality of patients with an acute coronary syndrome
Authors
D.B. Panagiotakos Pitsavos, C. Georgousopoulou, E.N. Notara, V. Stefanadis, C.
Publication date
1 January 2015
Publisher
Abstract
Background and Objectives: Risk evaluation of patients hospitalized with acute coronary syndrome (ACS) may contribute to their short-term prognosis improvement. The aim of this work was to develop a prediction index (score) for the risk assessment of 30-day death of ACS patients, using clinical and biological measurements at hospital admission. Methods: A sample of 6 Greek hospitals was selected, and almost all consecutive 2172 ACS patients from October 2003 to September 2004 were enrolled. Sociodemographic, biochemical, clinical, and lifestyle characteristics were recorded. Using as components age, systolic blood pressure, white blood cell count, creatine kinase-MB, and creatinine levels at the time of admission and the time between the onset of symptoms and presentation at hospital, a risk score (Greek Acute Coronary Syndrome score; range, 6-36) was developed and tested against in-hospital and 30-day outcome of the patients. Results: The Greek Acute Coronary Syndrome score showed strong discriminating ability for in-hospital mortality (area under the receiver operating characteristic curve, 0.812; 95% confidence interval, 0.750-0.874; P <.001) and 30-day death after hospitalization (area under the receiver operating characteristic curve, 0.720; 95% confidence interval, 0.724-0.837; P <.001). The optimal value of the score, which discriminates those who will die in-hospital from survivors, was 24, and that for those who will die within 30 days after discharge was 22. The score's classification ability was confirmed using 100 bootstrap samples and remained similar among several subgroups of patients (younger or older, men or women, type of ACS, and diabetes status). Conclusions: The suggested risk score using routinely collected clinical and biological data may be a useful tool in clinical practice for decision making regarding further management, not only during hospitalization but also in the postdischarge period. © 2015 Wolters Kluwer Health, Inc
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Last time updated on 10/02/2023