Recently, a predictive model has been developed to assess the risk of myocardial infarction or cardiac arrest (MICA) during and after surgery using the American Society of Surgeons' National Surgical Quality Improvement Program (NSQIP) database. In this MICA model, 180 hospital databases were used in 2007 and 2008 and included more than 200 000 patients. The Gupta score developed with this MICA model identified five predictors of perioperative myocardial infarction and cardiac arrest: type of surgery, functional status, creatinine increase (\>130 mmol/L or \>1.5 mg/dL), age, and American Association of Anesthesiologists (ASA) class. The Gupta score is presented as an interactive risk calculation program in the 2014 guideline of the ACC/AHA. The risk can be calculated simply and accurately at the bedside or clinic. The Gupta score is in spreadsheet format and can be downloaded online at http://www.surgicalriskcalculator.com/miorcardiacarrest. Unlike the previously used indexes, a scoring system has not been established. An estimate of the probability of myocardial infarction/cardiac arrest is provided for individual patients. In this study, the primary aim was to compare the frequency of cardiology consultation requests according to the use of the Gupta score. The secondary aim is to evaluate the perioperative clinical results (coronary angiography, ECHO, acute coronary syndrome, arrhythmia, 30-day mortality, etc.).SPSS 21.0 (Version 22.0, SPSS, Inc, Chicago, IL, USA) program will be used for statistical analysis. After applying the Shapiro-Wilk test for normality, the student's t-test will be used if the distribution is normal, and the Mann-Whitey U test will be used if the distribution is not normal. Fisher's exact test or chi-square test will be used for categorical variables. Results p\<0.05 will be considered significant.
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Gupta score
Timeframe: perioperative period