Paper
Saturday, July 16, 2005
Impact of Perioperative Temperature on Postoperative Surgical Site Infections: Improving the Predictability of Standard Risk Indices
Hanako Misao, RN, NM, PHN, MSN, PhD, Clinical practice evaluation and research center, St. Luke's Life Science Institute, Tokyo, Japan and Mary Castle White, RN, MPH, PhD, FAAN, Department of Community Health Systems, University of California, San Francisco, School of Nursing, San Francisco, CA, USA.
| Learning Objective #1: Understand the effect of perioperative temperature on the incidence of surgical site infections (SSIs) |
| Learning Objective #2: Understand perioperative temperature in addition to the existing risk indices as a nursing tool to improve the prediction of SSIs |
This retrospective cohort study was designed to examine the impact of perioperative temperature on prediction of postoperative surgical site infections (SSIs) among general abdominal surgical patients. The current extant risk indices, Study on the Efficacy of Nosocomial Infection Control (SENIC) and National Nosocomial Infection Surveillance (NNIS) risk indices, and a modified risk index, in which a factor related to perioperative temperature was added to the extant risk indices, were compared in terms of predictability of SSIs. Total medical chart review within 30 days after surgery was done on 230 patients undergoing abdominal surgery. SSIs were identified using Centers for Disease Control and Prevention definitions. Cumulative SSI incidence was 22.6%. Intraoperative core temperatures were measured at the following points: initial and final core temperatures, the lowest core temperature, and the minutes of the core temperature less than 35°C. Unlike the findings of previous studies, none of these measurements reached statistical significance. However, the difference between the initial and the final core temperatures (p=0.001) as well as the difference between the initial and the lowest core temperatures (p=0.031) were statistically significant between patients with and without SSIs. Both the SENIC (p<0.01) and NNIS (p<0.01) risk indices were good predictors for postoperative SSIs. Logistic regression analysis showed that the change between the initial and the final core temperatures, controlling for the influence of the perioperative factors including each risk index, was an important predictor of SSIs: adjusted Odds Ratio (AOR) = 2.923 for temperature change when added to SENIC factors; AOR = 2.101 for temperature change when added to NNIS factors. The addition of temperature change during surgery to the extant risk indices for SSIs both improves the ability to predict this serious adverse event and provides nurses and other healthcare workers with a potentially modifiable factor to reduce risk.