Impact of the Choice of Risk Model for Identifying Low-risk Patients Using the 2014 American College of Cardiology/American Heart Association Perioperative Guidelines. (November 2018)

• Record Type: Journal Article
• Authors: Glance, Laurent G.; Faden, Eric; Dutton, Richard P.; Lustik, Stewart J.; Li, Yue; Eaton, Michael P.; Dick, Andrew W.
• Is Part Of: Anesthesiology. Volume 129:Number 5(2018)
• Publication Date: 2018-11
• Subjects: Anesthesiology -- Periodicals; Anesthetics -- Periodicals; Anesthesia -- Periodicals; 617.9605
• DOI: 10.1097/ALN.0000000000002341
• Languages: English
• ISSNs: 0003-3022

Abstract

Editor's Perspective: What We Already Know about This Topic: The Revised Cardiac Risk Index, and the risk calculators based on the National Surgical Quality Improvement Program can be used to assess the risk of cardiac adverse events after noncardiac surgery Recent clinical practice guidelines recommend the use of one of these calculators The agreement across these calculators is poorly understood and has not been robustly tested in a single analysis What This Article Tells Us That Is New: Thirty percent of predictions regarding high versus low risk are discordant across the risk calculators The choice of risk-prediction tool could have an impact on the calculated risk and subsequent clinical decisions Background: The 2014 American College of Cardiology Perioperative Guideline recommends risk stratifying patients scheduled to undergo noncardiac surgery using either: (1) the Revised Cardiac Index; (2) the American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator; or (3) the Myocardial Infarction or Cardiac Arrest calculator. The aim of this study is to determine how often these three risk-prediction tools agree on the classification of patients as low risk (less than 1%) of major adverse cardiac event. Methods: This is a retrospective observational study using a sample of 10, 000 patient records. The risk of cardiac complications was calculated for the Revised Cardiac Index and the Myocardial Infarction or Cardiac Arrest models using published coefficients, and for the American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator using the publicly available website. The authors used the intraclass correlation coefficient and kappa analysis to quantify the degree of agreement between these three risk-prediction tools. Results: There is good agreement between the American College of Surgeons National Surgical Quality Improvement Program and Myocardial Infarction or Cardiac Arrest estimates of major adverse cardiac events (intraclass correlation coefficient = 0.68, 95% CI: 0.66 to 0.70), while only poor agreement between (1) American College of Surgeons National Surgical Quality Improvement Program Surgical Risk Calculator and the Revised Cardiac Index (intraclass correlation coefficient = 0.37; 95% CI: 0.34 to 0.40), and (2) Myocardial Infarction or Cardiac Arrest and Revised Cardiac Index (intraclass correlation coefficient = 0.26; 95% CI: 0.23 to 0.30). The three prediction models disagreed 29% of the time on which patients were low risk. Conclusions: There is wide variability in the predicted risk of cardiac complications using different risk-prediction tools. Including more than one prediction tool in clinical guidelines could lead to differences in decision-making for some patients depending on which risk calculator is used. Abstract : Thirty percent of predictions regarding high versus low risk are discordant across the risk calculators. The choice of riskprediction tool could have an impact on the calculated risk and subsequent clinical decisions.Supplemental Digital Content is available in the text.