Newly Published
Perioperative Medicine  |   July 2018
Impact of the Choice of Risk Model for Identifying Low-risk Patients Using the 2014 American College of Cardiology/American Heart Association Perioperative Guidelines
Author Notes
  • From the Department of Anesthesiology (L.G.G., E.F., S.J.L., M.P.E.) and the Department of Public Health Sciences (L.G.G., Y.L.), University of Rochester School of Medicine, Rochester, New York; RAND Health, Boston, Massachusetts (L.G.G., A.W.D.); and U.S. Anesthesia Partners, Dallas, Texas (R.P.D.).
  • Supplemental Digital Content is available for this article. Direct URL citations appear in the printed text and are available in both the HTML and PDF versions of this article. Links to the digital files are provided in the HTML text of this article on the Journal’s Web site (www.anesthesiology.org).
    Supplemental Digital Content is available for this article. Direct URL citations appear in the printed text and are available in both the HTML and PDF versions of this article. Links to the digital files are provided in the HTML text of this article on the Journal’s Web site (www.anesthesiology.org).×
  • Submitted for publication July 7, 2017. Accepted for publication June 5, 2018.
    Submitted for publication July 7, 2017. Accepted for publication June 5, 2018.×
  • Research Support: Supported by funding from the Department of Anesthesiology at the University of Rochester School of Medicine, Rochester, New York.
    Research Support: Supported by funding from the Department of Anesthesiology at the University of Rochester School of Medicine, Rochester, New York.×
  • Competing Interests: The authors declare no competing interests.
    Competing Interests: The authors declare no competing interests.×
  • Correspondence: Address correspondence to Dr. Glance: University of Rochester Medical Center, 601 Elmwood Avenue, Box 604, Rochester, New York 14642. Laurent_Glance@urmc.rochester.edu. Information on purchasing reprints may be found at www.anesthesiology.org or on the masthead page at the beginning of this issue. Anesthesiology’s articles are made freely accessible to all readers, for personal use only, 6 months from the cover date of the issue.
Article Information
Perioperative Medicine
Perioperative Medicine   |   July 2018
Impact of the Choice of Risk Model for Identifying Low-risk Patients Using the 2014 American College of Cardiology/American Heart Association Perioperative Guidelines
Anesthesiology Newly Published on July 11, 2018. doi:10.1097/ALN.0000000000002341
Anesthesiology Newly Published on July 11, 2018. doi:10.1097/ALN.0000000000002341
Abstract

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.