• J. Vasc. Surg. · Sep 2010

    Comparative Study

    The Vascular Study Group of New England Cardiac Risk Index (VSG-CRI) predicts cardiac complications more accurately than the Revised Cardiac Risk Index in vascular surgery patients.

    • Daniel J Bertges, Philip P Goodney, Yuanyuan Zhao, Andres Schanzer, Brian W Nolan, Donald S Likosky, Jens Eldrup-Jorgensen, Jack L Cronenwett, and Vascular Study Group of New England.
    • Divisions of Vascular Surgery of University of Vermont College of Medicine, Burlington, Vt 05401, USA. daniel.bertges@vtmednet.org
    • J. Vasc. Surg. 2010 Sep 1;52(3):674-83, 683.e1-683.e3.

    ObjectiveThe Revised Cardiac Risk Index (RCRI) is a widely used model for predicting cardiac events after noncardiac surgery. We compared the accuracy of the RCRI with a new, vascular surgery-specific model developed from patients within the Vascular Study Group of New England (VSGNE).MethodsWe studied 10,081 patients who underwent nonemergent carotid endarterectomy (CEA; n = 5293), lower extremity bypass (LEB; n = 2673), endovascular abdominal aortic aneurysm repair (EVAR; n = 1005), and open infrarenal abdominal aortic aneurysm repair (OAAA; n = 1,110) within the VSGNE from 2003 to 2008. First, we analyzed the ability of the RCRI to predict in-hospital major adverse cardiac events, including myocardial infarction (MI), arrhythmia, or congestive heart failure (CHF) in the VSGNE cohort. Second, we used a derivation cohort of 8208 to develop a new cardiac risk prediction model specifically for vascular surgery patients. Chi-square analysis identified univariate predictors, and multivariate logistic regression was used to develop an aggregate and four procedure-specific risk prediction models for cardiac complications. Calibration and model discrimination were assessed using Pearson correlation coefficient and receiver operating characteristic (ROC) curves. The ability of the model to predict cardiac complications was assessed within a validation cohort of 1873. Significant predictors were converted to an integer score to create a practical cardiac risk prediction formula.ResultsThe overall incidence of major cardiac events in the VSGNE cohort was 6.3% (2.5% MI, 3.9% arrhythmia, 1.8% CHF). The RCRI predicted risk after CEA reasonably well but substantially underestimated risk after LEB, EVAR, and OAAA for low- and higher-risk patients. Across all VSGNE patients, the RCRI underestimated cardiac complications by 1.7- to 7.4-fold based on actual event rates of 2.6%, 6.7%, 11.6%, and 18.4% for patients with 0, 1, 2, and >or=3 risk factors. In multivariate analysis of the VSGNE cohort, independent predictors of adverse cardiac events were (odds ratio [OR]) increasing age (1.7-2.8), smoking (1.3), insulin-dependent diabetes (1.4), coronary artery disease (1.4), CHF (1.9), abnormal cardiac stress test (1.2), long-term beta-blocker therapy (1.4), chronic obstructive pulmonary disease (1.6), and creatinine >or=1.8 mg/dL (1.7). Prior cardiac revascularization was protective (OR, 0.8). Our aggregate model was well calibrated (r = 0.99, P < .001), demonstrating moderate discriminative ability (ROC curve = 0.71), which differed only slightly from the procedure-specific models (ROC curves: CEA, 0.74; LEB, 0.72; EVAR, 0.74; OAAA, 0.68). Rates of cardiac complications for patients with 0 to 3, 4, 5, and >or=6 VSG risk factors were 3.1%, 5.0%, 6.8%, and 11.6% in the derivation cohort and 3.8%, 5.2%, 8.1%, and 10.1% in the validation cohort. The VSGNE cardiac risk model more accurately predicted the actual risk of cardiac complications across the four procedures for low- and higher-risk patients than the RCRI. When the VSG Cardiac Risk Index (VSG-CRI) was used to score patients, six categories of risk ranging from 2.6% to 14.3% (score of 0-3 to 8) were discernible.ConclusionsThe RCRI substantially underestimates in-hospital cardiac events in patients undergoing elective or urgent vascular surgery, especially after LEB, EVAR, and OAAA. The VSG-CRI more accurately predicts in-hospital cardiac events after vascular surgery and represents an important tool for clinical decision making.

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