Risk factors for intraoperative hypothermia in patients receiving lung transplants.

BACKGROUND

Intraoperative hypothermia (IOH) has a high incidence in lung transplantation, which is considered to be an important factor affecting perioperative morbidity and mortality. Therefore, it is crucial to prevent IOH during lung transplantation. This study aimed to identify risk factors for IOH in patients receiving lung transplants, and to develop a risk model for predicting IOH.

METHODS

We collected data on 160 patients who received lung transplants at The First Affiliated Hospital, Guangzhou Medical University between January 2019 and October 2023. The patients were divided into a hypothermic group (n=106) and non-hypothermic group (n=54) based on whether or not they developed IOH. We built a logistic regression model and used a nomogram to investigate the risk of IOH. The predictive power of the model was evaluated using the receiver operating characteristics (ROC) curve and the calibration curve.

RESULTS

The incidence rate of IOH was 66.25%. Volume of intraoperative fluid [odds ratio (OR) =1.001, 95% confidence interval (CI): 1.000649 to 1.002, P<0.001] was associated with increased risk of developing IOH during lung transplantation, while extracorporeal membrane oxygenation (ECMO) (OR =0.091, 95% CI: 0.036 to 0.229, P<0.001) and circulating-water mattress (OR =0.389, 95% CI: 0.178 to 0.852, P=0.02) were protective factors against IOH. Compared to normothermic patients, patients with IOH were associated with the occurrence of cardiac arrhythmias, but was no difference in the length of stay (LOS) in the intensive care unit (ICU), acute kidney injury (AKI), postoperative hemorrhage, or 30-day mortality. The Hosmer-Lemeshow test yielded a P value of 0.18. The area under the ROC curve was 0.820, indicating that the model had good diagnostic efficacy. Similarly, evaluation of the nomogram using a calibration curve showed that the model had good accuracy in predicting IOH.

CONCLUSIONS

Owing to its strong predictive value, this risk prediction model can be used as a guide in clinical practice for screening individuals at high risk of IOH during lung transplantation.