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Surgical Risk Preoperative Assessment System (SURPAS): I. Parsimonious, Clinically Meaningful Groups of Postoperative Complications by Factor Analysis

Meguid, Robert A. MD, MPH; Bronsert, Michael R. PhD, MS; Juarez-Colunga, Elizabeth PhD; Hammermeister, Karl E. MD; Henderson, William G. MPH, PhD

doi: 10.1097/SLA.0000000000001669
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Objective: To use factor analysis to cluster the 18 American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) perioperative complications into a reproducible, smaller number of clinically meaningful groups of postoperative complications, facilitating and streamlining future study and application in live clinical settings.

Background: The ACS NSQIP collects and reports on eighteen 30-day postoperative complications (excluding mortality), which are variably grouped in published analyses using ACS NSQIP data. This hinders comparison between studies of this widely used quality improvement dataset.

Methods: Factor analysis was used to develop a series of complication clusters, which were then analyzed to identify a parsimonious, clinically meaningful grouping, using 2,275,240 surgical cases in the ACS NSQIP Participant Use File (PUF), 2005 to 2012. The main outcome measures are reproducible, data-driven, clinically meaningful clusters of complications derived from factor solutions.

Results: Factor analysis solutions for 5 to 9 latent factors were examined for their percent of total variance, parsimony, and clinical interpretability. Applying the first 2 of these criteria, we identified the 7-factor solution, which included clusters of pulmonary, infectious, wound disruption, cardiac/transfusion, venous thromboembolic, renal, and neurological complications, as the best solution for parsimony and clinical meaningfulness. Applying the last (clinical interpretability), we combined the wound disruption with the infectious clusters resulting in 6 clusters for future clinical applications.

Conclusions: Factor analysis of ACS NSQIP postoperative complication data provides 6 clinically meaningful complication clusters in lieu of 18 postoperative morbidities, which will facilitate comparisons and clinical implementation of studies of postoperative morbidities.

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*Surgical Outcomes and Applied Research Program, University of Colorado School of Medicine, Aurora

Department of Surgery, University of Colorado School of Medicine, Aurora

Adult and Child Center for Health Outcomes Research and Delivery Science, University of Colorado School of Medicine, Aurora

§Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora

Division of Cardiology, Department of Medicine, University of Colorado School of Medicine, Aurora.

Reprints: Robert A. Meguid, MD, MPH FACS, Division of Cardiothoracic Surgery, Department of Surgery, University of Colorado Denver, Anschutz Medical Campus, 12631 E 17th Ave, C-310, Aurora, CO 80045. E-mail: ROBERT.MEGUID@UCDenver.edu.

Robert A. Meguid and Michael R. Bronsert are co-first authors.

The present study was supported by the Department of Surgery, Adult and Child Center for Health Outcomes Research and Delivery Science Joint Surgical Outcomes and Applied Research Program at the University of Colorado, and by Dr Meguid's Academic Enrichment fund from the Department of Surgery.

Disclosure: All of the authors had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. The American College of Surgeons National Surgical Quality Improvement Program and participating hospitals are the source of these data; they have not verified and are not responsible for the statistical validity of the data analysis or the conclusions derived by the authors. The authors report no conflicts of interest.

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