Prediction of major cardiac events after vascular surgery

J Vasc Surg. 2017 Dec;66(6):1826-1835.e1. doi: 10.1016/j.jvs.2017.05.100. Epub 2017 Aug 12.

Abstract

Objective: Predicting cardiac events is essential to provide patients with the best medical care and to assess the risk-benefit ratio of surgical procedures. The aim of our study was to evaluate the performance of the Revised Cardiac Risk Index (Lee) and the Vascular Study Group of New England Cardiac Risk Index (VSG) scores for the prediction of major cardiac events in unselected patients undergoing arterial surgery and to determine whether the inclusion of additional risk factors improved their accuracy.

Methods: The study prospectively enrolled 954 consecutive patients undergoing arterial vascular surgery, and the Lee and VSG scores were calculated. Receiver operating characteristic curves for each cardiac risk score were constructed and the areas under the curve (AUCs) compared. Two logistic regression models were done to determine new variables related to the occurrence of major cardiac events (myocardial infarction, heart failure, arrhythmias, and cardiac arrest).

Results: Cardiac events occurred in 120 (12.6%) patients. Both scores underestimated the rate of cardiac events across all risk strata. The VSG score had AUC of 0.63 (95% confidence interval [CI], 0.58-0.68), which was higher than the AUC of the Lee score (0.58; 95% CI, 0.52-0.63; P = .03). Addition of preoperative anemia significantly improved the accuracy of the Lee score to an AUC of 0.61 (95% CI, 0.58-0.67; P = .002) but not that of the VSG score.

Conclusions: The Lee and VSG scores have low accuracy and underestimate the risk of major perioperative cardiac events in unselected patients undergoing vascular surgery. The Lee score's accuracy can be increased by adding preoperative anemia. Underestimation of major cardiac complications may lead to incorrect risk-benefit assessments regarding the planned operation.

Publication types

  • Comparative Study
  • Multicenter Study
  • Observational Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Area Under Curve
  • Arteries / surgery*
  • Brazil
  • Chi-Square Distribution
  • Decision Support Techniques*
  • Female
  • Heart Diseases / diagnosis
  • Heart Diseases / etiology*
  • Humans
  • Logistic Models
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Prospective Studies
  • ROC Curve
  • Registries
  • Risk Assessment
  • Risk Factors
  • Switzerland
  • Treatment Outcome
  • Vascular Surgical Procedures / adverse effects*