Validation of a Prediction Model for Intraoperative Hypothermia in Patients Receiving General Anesthesia

Abstract

Objectives. There have been no fully validated tools for the rapid identification of surgical patients at risk of intraoperative hypothermia. The objective of this study was to validate the performance of a previously established prediction model in estimating the risk of intraoperative hypothermia in a prospective cohort. Methods. In this observational study, consecutive adults scheduled for elective surgery under general anesthesia were enrolled prospectively at a tertiary hospital between September 4, 2020, and December 28, 2020. An intraoperative hypothermia risk score was calculated by a mobile application of the prediction model. A wireless axillary thermometer was used to continuously measure perioperative core temperature as the reference standard. The discrimination and calibration of the model were assessed, using the area under the receiver operating characteristic curve (AUC), Hosmer–Lemeshow goodness-of-fit test, and Brier score. Results. Among 227 participants, 99 (43.6%) developed intraoperative hypothermia, and 10 (4.6%) received intraoperative active warming with forced-air warming. The model had an AUC of 0.700 (95% confidence interval [CI], 0.632–0.768) in the overall cohort with adequate calibration (Hosmer–Lemeshow χ2 = 13.8, $P=0.087$ ; Brier score = 0.33 [95% CI, 0.29–0.37]). We categorized the risk scores into low-risk, moderate-risk, and high-risk groups, in which the incidence of intraoperative hypothermia was 23.0% (95% CI, 12.4–33.5), 43.4% (95% CI, 33.7–53.2), and 62.7% (95% CI, 51.5–74.3), respectively ( $P$ for trend <0.001). Conclusions. The intraoperative hypothermia prediction model demonstrated possibly helpful discrimination and adequate calibration in our prospective validation. These findings suggest that the risk screening model could facilitate future perioperative temperature management.