How can the occurrence of intraoperative hypothermia be predicted before surgery in gynecological surgery patients?

To address this issue, we conducted a multicenter cohort study of 802 patients who underwent gynecological surgery.

A powerful model was established for the early identification of patients prone to intraoperative hypothermia.

Hypothermia is highly common in patients undergoing gynecological surgeries under general anesthesia, so the length of hospitalization and even the risk of mortality are substantially increased. Our aim was to develop a simple and practical model to preoperatively identify gynecological surgery patients at risk of intraoperative hypothermia.

In this retrospective study, we collected data from 802 patients who underwent gynecological surgery at three medical centers from June 2022 to August 2023. We further allocated the patients to a training group, an internal validation group, or an external validation group. The preliminary predictive factors for intraoperative hypothermia in gynecological patients were determined using the least absolute shrinkage and selection operator (LASSO) method. The final predictive factors were subsequently identified through multivariate logistic regression analysis, and a nomogram for predicting the occurrence of hypothermia was established.

A total of 802 patients were included, with 314 patients in the training cohort (mean age 48.5 ± 12.6 years), 130 patients in the internal validation cohort (mean age 49.9 ± 12.5 years), and 358 patients in the external validation cohort (mean age 47.6 ± 14.0 years). LASSO regression and multivariate logistic regression analyses indicated that body mass index, minimally invasive surgery, baseline heart rate, baseline body temperature, history of previous surgery, and aspartate aminotransferase level were associated with intraoperative hypothermia in gynecological surgery patients. This nomogram was constructed based on these six variables, with a C-index of 0.712 for the training cohort.

We established a practical predictive model that can be used to preoperatively predict the occurrence of hypothermia in gynecological surgery patients.

Clinical trial registration: chictr.org.cn, identifier ChiCTR2300071859.

Gynecological surgery

Hypothermia

Predictive model

Multi-center study

alanine aminotransferase

activated partial thromboplastin time

American Society of Anesthesiologists

aspartate aminotransferase

area under the receiver operating characteristic curve

decision curve analysis

international normalized ratio

least absolute shrinkage and selection operator

mean arterial pressure

postanesthesia care unit

© 2024 The Authors. Published by Elsevier Inc.