The Vascular Quality Initiative Cardiac Risk Index for prediction of myocardial infarction after vascular surgery

Abstract

Objective The objective of this study was to develop and to validate the Vascular Quality Initiative (VQI) Cardiac Risk Index (CRI) for prediction of postoperative myocardial infarction (POMI) after vascular surgery. Methods We developed risk models for in-hospital POMI after 88,791 nonemergent operations from the VQI registry, including carotid endarterectomy (CEA; n = 45,340), infrainguinal bypass (INFRA; n = 18,054), suprainguinal bypass (SUPRA; n = 2678), endovascular aneurysm repair (EVAR; n = 18,539), and open abdominal aortic aneurysm repair (OAAA repair; n = 4180). Multivariable logistic regression was used to create an all-procedure and four procedure-specific risk calculators based on the derivation cohort from 2012 to 2014 (N = 61,236). Generalizability of the all-procedure model was evaluated by applying it to each procedure subtype. The models were validated using a cohort (N = 27,555) from January 2015 to February 2016. Model discrimination was measured by area under the receiver operating characteristic curve (AUC), and performance was validated by bootstrapping 5000 iterations. The VQI CRI calculator was made available on the Internet and as a free smart phone app available through QxCalculate. Results Overall POMI incidence was 1.6%, with variation by procedure type as follows: CEA, 0.8%; EVAR, 1.0%; INFRA, 2.6%; SUPRA, 3.1%; and OAAA repair, 4.3% (P < .001). Predictors of POMI in the all-procedure model included age, operation type, coronary artery disease, congestive heart failure, diabetes, creatinine concentration >1.8 mg/dL, stress test status, and body mass index (AUC, 0.75; 95% confidence interval =CI], 0.73-0.76). The all-procedure model demonstrated only minimally reduced accuracy when it was applied to each procedure, with the following AUCs: CEA, 0.65 (95% CI, 0.59-0.70); INFRA, 0.69 (95% CI, 0.64-0.73); EVAR, 0.72 (95% CI, 0.65-0.80); SUPRA, 0.62 (95% CI, 0.52-0.72); and OAAA, 0.63 (95% CI, 0.56-0.70). Procedure-specific models had unique predictors and showed improved prediction compared with the all-procedure model, with the following AUCs: CEA, 0.69 (95% CI, 0.66-0.72); INFRA, 0.75 (95% CI, 0.73-0.78); EVAR, 0.76 (95% CI, 0.73-0.80); and OAAA, 0.72 (95% CI, 0.69-0.77). Bias-corrected AUC (95% CI) from internal validation for the models was as follows: all procedures, 0.75 (0.73-0.76); CEA, 0.68 (0.65-0.71); INFRA, 0.74 (0.72-0.76); EVAR, 0.73 (0.70-0.78); and OAAA repair, 0.68 (0.65-0.73). Conclusions The VQI CRI is a useful and valid clinical decision-making tool to predict POMI after vascular surgery. Procedure-specific models improve accuracy when they include unique risk factors.

Prediction of major cardiac events after vascular surgery

“…26 In a recent registry that included 88,791 patients submitted to nonemergent vascular operations, the overall incidence of MI was 1.6%. 17 Previous studies also reported lower overall procedure-specific perioperative MI rates than ours, most likely because of better surveillance in our prospective study. 19,21 As there is no specific universal definition for MI after noncardiac surgery, the difference in incidence of MI in several studies depends on the diagnostic criteria and the cardiac troponin assay used.…”

“…These scores have to be done online or using mobile applications and evaluate only risk of MI and cardiac death, both factors limiting practical clinical use. 17,21,43 Currently, with improvement of surgical and anesthetic techniques, patients undergoing noncardiac surgery are increasingly older and have more comorbidities; therefore, it is also important to estimate the risk of other common cardiac complications besides MI and cardiac arrest, such as AHF and arrhythmias. All risk prediction scores have advantages and limitations.…”

“…For our secondary analysis, to determine new variables independently related to the occurrence of cardiac events after surgery, two binary logistic regression models for each score were created including the scores and variables preselected by literature research (urgency, anemia, preoperative medication use). [6][7][8][9]11,[17][18][19][20][21] As power estimation for our regression analysis, we chose to include a maximum number of covariables of 1 variable per 10 events. 22 The same variables were included in both models, except for variables that were already part of the respective score, such as type of surgery in the Lee score or smoking status in the VSG score.…”

Regional Variation in Postoperative Myocardial Infarction in Patients Undergoing Vascular Surgery in the United States

“…7 Because variation in POMI may be due to a number of factors including procedure type and patient comorbidities, notably renal insufficiency, diabetes, and preexisting coronary artery disease, risk adjustment was performed using the previously established VQI CRI (Cardiac Risk Index) all-procedures risk prediction model. 8 …”

Utility of the Vascular Quality Initiative in improving quality of care in Canadian patients undergoing vascular surgery

“…The VQI has been shown to be an important tool in quality improvement in the United States and now in Canada. 9,10 It allows real-time benchmarking of individual phys icians and centres against local, regional and national trends. The VQI is a powerful tool for vascular surgeons as it was engineered specifically for vascular surgery.…”