Elsevier

Journal of Vascular Surgery

Volume 52, Issue 3, September 2010, Pages 674-683.e3
Journal of Vascular Surgery

Clinical research study
From the New England Society for Vascular Surgery
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

Presented at the Thirty-sixth Annual New England Society for Vascular Surgery, Boston, Mass, Oct 3, 2009.
https://doi.org/10.1016/j.jvs.2010.03.031Get rights and content
Under an Elsevier user license
open archive

Objective

The 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).

Methods

We 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.

Results

The 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 ≥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 β-blocker therapy (1.4), chronic obstructive pulmonary disease (1.6), and creatinine ≥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 ≥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.

Conclusions

The 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.

Cited by (0)

Supported in part by a grant from the Center for Medicare and Medicaid Services.

Competition of interest: None.

The editors and reviewers of this article have no relevant financial relationships to disclose per the JVS policy that requires reviewers to decline review of any manuscript for which they may have a competition of interest.

Additional material for this article may be found online at www.jvascsurg.org.