Web-Based Model Shows Promise for Predicting Stroke, Cardiac Events after Non-Cardiac Surgery

A web-based model developed by a team at Thomas Jefferson University appeared to accurately predict risk of stroke and adverse cardiovascular events following non-cardiac surgery.

A new study from Thomas Jefferson University is providing evidence in support of their prediction model for determining risk of stroke and other cardiovascular complications in patients undergoing non-cardiac surgery.

Results of the study indicate the web-based model could help identify patients at high-risk for these events and allow clinicians the ability to circumvent this risk when possible.

"Often times we do the research and publish a research paper that is too complex to translate to the bedside," said lead investigator Sang Woo, MD, director of the Division of Hospital Medicine at Thomas Jefferson University, in a statement. "My goal from the beginning was to come up with a new model that is very practical and useful and that can be incorporated into routine patient care."

Despite advances in technology and monitoring, cardiovascular complications following non-cardiac surgery remain a significant risk for many. With this in mind, the current study was designed as a way to validate a prediction model developed by Woo and a team of colleagues from Thomas Jefferson to assess risk for these events.

Woo and team designed their model using data from the Universal American College of Surgeons National Surgical Quality Improvement Program (ACS‐NSQIP). Specifically, the model was developed based on a cohort of 809,880 patients treated between 2007-2009. The model was created using information related to the age, history of coronary artery disease, history of stroke, emergency surgery, preoperative serum sodium, creatinine, hematocrit, American Society of Anesthesiologists physical status class, and type of surgery. This model was subsequently tested using ACS-NSQIP data from 2010.

The primary outcomes of interest for the study were postoperative 30-day stroke, major cardiovascular events, and 30-day mortality. For the purpose of analysis, major cardiovascular events included myocardial infarction, cardiac arrest, or stroke.

In the cohort of 355,870 patients from 2010 used to test the model, major cardiac complications occurred in 0.66% (n=5332) of patients (myocardial infarction, 0.28%; cardiac arrest, 0.41%), postoperative stroke occurred in in 0.25% (n=2005), and 30‐day mortality was 1.66% (n=13,484). Upon analysis, result indicated the risk prediction model had high predictive accuracy with area under the receiver operating characteristic curve for stroke (training cohort=0.869, validation cohort=0.876), major cardiovascular events (training cohort=0.871, validation cohort=0.868), and 30‐day mortality (training cohort=0.922, validation cohort=0.925).

Further analysis indicated surgery types, history of stroke, and coronary artery disease appeared to be significant risk factors for stroke and major cardiac complications. The surgery types associated with highest risk of stroke were vascular (thoracic‐EVAR), brain surgery, and carotid endarterectomy. For cardiac complications, procedures associated with greatest risk were open aorta surgery, thoracic‐EVAR, suprainguinal bypass, intestinal surgery, and liver/pancreas/spleen surgery.

“Using 9 clinical variables in a national cohort of patient data from the robust ACS‐NSQIP database collected over 4 years, we developed and validated a clinically useful risk assessment model for stroke, cardiac, and mortality risk,” wrote investigators in their conclusion.

This study, “Development and Validation of a Prediction Model for Stroke, Cardiac, and Mortality Risk After Non‐Cardiac Surgery,” was published in the Journal of the American Heart Association.