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Development and validation of a risk calculator for prediction of cardiac risk after surgery
Prateek K Gupta1, Himani Gupta, Abhishek Sundaram
1Department of Surgery, Creighton University, 601 N 30th St, Omaha, NE 68131, USA. prateekgupta@creighton.edu
Insights
A new cardiac risk calculator was developed to predict perioperative myocardial infarction or cardiac arrest. This tool offers improved accuracy over the Revised Cardiac Risk Index, aiding informed consent for surgical patients.
Area of Science:
- Cardiology
- Anesthesiology
- Health Informatics
Background:
- Perioperative myocardial infarction and cardiac arrest lead to significant patient morbidity and mortality.
- The Revised Cardiac Risk Index (RCRI) is a widely used tool but has limited predictive accuracy.
- There is a need for improved risk stratification tools in cardiac surgery.
Purpose of the Study:
- To develop and validate a novel predictive cardiac risk calculator.
- To improve the accuracy of risk assessment for perioperative cardiac events.
- To create a tool that simplifies the informed consent process for patients undergoing surgery.
Main Methods:
- Utilized the American College of Surgeons' National Surgical Quality Improvement Program database (2007 and 2008).
- Identified predictors of perioperative myocardial infarction or cardiac arrest using multivariate logistic regression.
- Validated the developed risk model on an independent dataset.
Main Results:
- Identified five key predictors: surgery type, functional status, creatinine levels, ASA class, and age.
- The developed risk calculator demonstrated high predictive performance (C-statistics of 0.884 and 0.874).
- The new calculator significantly outperformed the RCRI (C-statistic 0.747).
Conclusions:
- The developed cardiac risk calculator accurately estimates the risk of perioperative myocardial infarction or cardiac arrest.
- This tool is expected to enhance the informed consent process for surgical procedures.
- The novel calculator offers superior predictive ability compared to the existing RCRI.
Background:
Perioperative myocardial infarction or cardiac arrest is associated with significant morbidity and mortality. The Revised Cardiac Risk Index is currently the most commonly used cardiac risk stratification tool; however, it has several limitations, one of which is its relatively low discriminative ability. The objective of the present study was to develop and validate a predictive cardiac risk calculator.
Methods And Results:
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. Of the 211 410 patients, 1371 (0.65%) developed perioperative myocardial infarction or cardiac arrest. On multivariate logistic regression analysis, 5 predictors of perioperative myocardial infarction or cardiac arrest were identified: type of surgery, dependent functional status, abnormal creatinine, American Society of Anesthesiologists' 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 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 cardiac risk calculator provides a risk estimate of perioperative myocardial infarction or cardiac arrest and is anticipated to simplify the informed consent process. Its predictive performance surpasses that of the Revised Cardiac Risk Index.
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