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Development and Validation of a Risk Calculator for Prediction of Cardiac Risk After Surgery
Study Questions:
What are the risk factors associated with intraoperative/postoperative myocardial infarction (MI) or cardiac arrest (CA), and can a risk calculator be developed and validated for its prediction?
Methods:
Patients who underwent surgery were identified from the American College of Surgeons’ 2007 National Surgical Quality Improvement Program database, a multicenter (>250 hospitals) prospective database. The primary endpoint was intraoperative/postoperative MI or CA through 30 days after surgery. Stepwise multivariate logistic regression was performed to assess the most parsimonious combination of risk factors predictive of MI or CA, thus creating the full model.
Results:
Of the 211,410 patients, 1,371 (0.65%) developed perioperative MI or CA. On multivariate logistic regression analysis, five predictors of perioperative MI or CA were identified: type of surgery, dependent functional status, abnormal creatinine, American Society of Anesthesiologists’ (ASA) class, and increasing age. The risk model based on the 2007 data set was subsequently validated on the 2008 data set (n = 257,385). The model performance was very similar between the 2007 and 2008 data sets, with c-statistics (also known as area under the receiver operating characteristic curve) of 0.884 and 0.874, respectively. Application of the Revised Cardiac Risk Index (RCRI) to the 2008 National Surgical Quality Improvement Program data set yielded a relatively lower c-statistic (0.747). The risk model was used to develop an interactive risk calculator.
Conclusions:
The authors concluded that the cardiac risk calculator provides a risk estimate of perioperative MI or CA.
Perspective:
The study suggests that ASA class, dependent functional status, age, abnormal creatinine (>1.5 mg/dl), and type of surgery were associated with cardiac risk after surgery. A cardiac risk calculator was developed based on these predictors, and had a much higher discriminative value when compared to the RCRI, currently the most commonly used cardiac risk stratification tool. Although fewer than 1% of patients develop MI or CA, approximately two thirds of these patients die within 30 days of surgery. This high mortality rate seen in patients with MI or CA underscores the importance of appropriate risk stratification and preoperative optimization. The risk calculator, developed using parameters from this study with its high discriminative ability for intraoperative/postoperative MI or CA, will also help simplify the informed consent process.
Keywords: Myocardial Infarction, Risk Factors, Heart Arrest, Creatinine, Vascular Surgical Procedures, United States
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