An evaluation of surgical site infections by wound classification system using the ACS-NSQIP

J Surg Res. 2012 May 1;174(1):33-8. doi: 10.1016/j.jss.2011.05.056. Epub 2011 Jun 24.

Abstract

Background: Surgical wound classification has been the foundation for infectious risk assessment, perioperative protocol development, and surgical decision-making. The wound classification system categorizes all surgeries into: clean, clean/contaminated, contaminated, and dirty, with estimated postoperative rates of surgical site infection (SSI) being 1%-5%, 3%-11%, 10%-17%, and over 27%, respectively. The present study evaluates the associated rates of the SSI by wound classification using a large risk adjusted surgical patient database.

Methods: A cross-sectional study was performed using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) dataset between 2005 and 2008. All surgical cases that specified a wound class were included in our analysis. Patient demographics, hospital length of stay, preoperative risk factors, co-morbidities, and complication rates were compared across the different wound class categories. Surgical site infection rates for superficial, deep incisional, and organ/space infections were analyzed among the four wound classifications using multivariate logistic regression.

Results: A total of 634,426 cases were analyzed. From this sample, 49.7% were classified as clean, 35.0% clean/contaminated, 8.56% contaminated, and 6.7% dirty. When stratifying by wound classification, the clean, clean/contaminated, contaminated, and dirty wound classifications had superficial SSI rates of 1.76%, 3.94%, 4.75%, and 5.16%, respectively. The rates of deep incisional infections were 0.54%, 0.86%, 1.31%, and 2.1%. The rates for organ/space infection were 0.28%, 1.87%, 2.55%, and 4.54%.

Conclusion: Using ACS-NSQIP data, the present study demonstrates substantially lower rates of surgical site infections in the contaminated and dirty wound classifications than previously reported in the literature.

MeSH terms

  • Adult
  • Aged
  • Cross-Sectional Studies
  • Female
  • Humans
  • Length of Stay
  • Logistic Models
  • Male
  • Middle Aged
  • Surgical Wound Infection / epidemiology*
  • Wounds and Injuries / classification