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The Surgical Mortality Probability Model: Derivation and Validation of a Simple Risk Prediction Rule for Noncardiac Surgery

Glance, Laurent G. MD*,†; Lustik, Stewart J. MD*; Hannan, Edward L. PhD; Osler, Turner M. MD§; Mukamel, Dana B. PhD; Qian, Feng MD,PhD*; Dick, Andrew W. PhD

Annals of Surgery:
doi: 10.1097/SLA.0b013e31824b45af
Original Articles
Abstract

Objective: To develop a 30-day mortality risk index for noncardiac surgery that can be used to communicate risk information to patients and guide clinical management at the “point-of-care,” and that can be used by surgeons and hospitals to internally audit their quality of care.

Background: Clinicians rely on the Revised Cardiac Risk Index to quantify the risk of cardiac complications in patients undergoing noncardiac surgery. Because mortality from noncardiac causes accounts for many perioperative deaths, there is also a need for a simple bedside risk index to predict 30-day all-cause mortality after noncardiac surgery.

Methods: Retrospective cohort study of 298,772 patients undergoing noncardiac surgery during 2005 to 2007 using the American College of Surgeons National Surgical Quality Improvement Program database.

Results: The 9-point S-MPM (Surgical Mortality Probability Model) 30-day mortality risk index was derived empirically and includes three risk factors: ASA (American Society of Anesthesiologists) physical status, emergency status, and surgery risk class. Patients with ASA physical status I, II, III, IV or V were assigned either 0, 2, 4, 5, or 6 points, respectively; intermediate- or high-risk procedures were assigned 1 or 2 points, respectively; and emergency procedures were assigned 1 point. Patients with risk scores less than 5 had a predicted risk of mortality less than 0.50%, whereas patients with a risk score of 5 to 6 had a risk of mortality between 1.5% and 4.0%. Patients with a risk score greater than 6 had risk of mortality more than 10%. S-MPM exhibited excellent discrimination (C statistic, 0.897) and acceptable calibration (Hosmer-Lemeshow statistic 13.0, P = 0.023) in the validation data set.

Conclusions: Thirty-day mortality after noncardiac surgery can be accurately predicted using a simple and accurate risk score based on information readily available at the bedside. This risk index may play a useful role in facilitating shared decision making, developing and implementing risk-reduction strategies, and guiding quality improvement efforts.

In Brief

Using data from the American College of Surgeons National Surgical Quality Improvement Program database, we developed a 30-day mortality risk index for noncardiac surgery. The 9-point Surgical Mortality Probability Model (S-MPM) 30-day mortality risk index was derived empirically and includes 3 risk factors: ASA (American Society of Anesthesiologists) physical status, emergency status, and surgery risk class. Patients with ASA physical status I, II, III, IV, or V were assigned either 0, 2, 4, 5, or 6 points, respectively; intermediate- or high-risk procedures were assigned 1 or 2 points, respectively; and emergency procedures were assigned 1 point. S-MPM exhibited excellent discrimination (C statistic, 0.897) and acceptable calibration (Hosmer-Lemeshow statistic 13.0, P = 0.023) in the validation data set.

Author Information

Departments of *Anesthesiology

Community and Preventive Medicine, University of Rochester School of Medicine, Rochester, NY

School of Public Health, Department of Health Policy, Management and Behavior, Albany, NY

§Department of Surgery, University of Vermont Medical College, Burlington, VT

Center for Health Policy Research, University of California, Irvine, CA

RAND, Pittsburgh, PA.

Reprints: Laurent G. Glance, MD, Department of Anesthesiology, University of Rochester Medical Center, 601 Elmwood Avenue, Box 604, Rochester, NY 14642. E-mail: Laurent_Glance@urmc.rochester.edu.

Disclosure: The authors declare no conflicts of interest.

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© 2012 Lippincott Williams & Wilkins, Inc.