Abstract
OBJECTIVE: To assess the incremental contribution of preoperative stress test results toward a diagnosis of obstructive coronary artery disease (CAD), prediction of mortality, or prediction of perioperative myocardial infarction in patients considering noncardiac, nonophthalmologic surgery. DESIGN, SETTING, PARTICIPANTS: A retrospective cohort study of visits to a preoperative risk assessment and optimization clinic in a large health system between 2008 and 2018. MEASUREMENTS: To assess diagnostic information of preoperative stress testing, we used the Begg and Greenes method to calculate test characteristics adjusted for referral bias, with a gold standard of angiography. To assess prognostic information, we first created multiply-imputed logistic regression models to predict 90-day mortality and perioperative myocardial infarction (MI), starting with two tools commonly used to assess perioperative cardiac risk, Revised Cardiac Risk Index (RCRI) and Myocardial Infarction or Cardiac Arrest (MICA). We then added stress test results and compared the discrimination for models with and without stress test results. MAIN RESULTS: Among 136,935 visits by patients without an existing diagnosis of CAD, the decision to obtain preoperative stress testing identified around 4.0% of likely new diagnoses. Stress testing increased the likelihood of CAD (likelihood ratio: 1.31), but for over 99% of patients, stress testing should not change a decision on whether to proceed to angiography. In 117,445 visits with subsequent noncardiac surgery, stress test results failed to improve predictions of either perioperative MI or 90-day mortality. Reweighting the models and adding hemoglobin improved the prediction of both outcomes. CONCLUSIONS: Cardiac stress testing before noncardiac, nonophthalmologic surgery does not improve predictions of either perioperative mortality or myocardial infarction. Very few patients considering noncardiac, nonophthalmologic surgery have a pretest probability of CAD in a range where stress testing could usefully select patients for angiography. Better use of existing patient data could improve predictions of perioperative adverse events without additional patient testing.