Effects of Female Reproductive Hormone Levels on Inadvertent Intraoperative Hypothermia during Laparoscopic Gynecologic Surgery: A Retrospective Study

Application value of machine learning models in predicting intraoperative hypothermia in laparoscopic surgery for polytrauma patients

BACKGROUND

Hypothermia during laparoscopic surgery in patients with multiple trauma is a significant concern owing to its potential complications. Machine learning models offer a promising approach to predict the occurrence of intraoperative hypothermia.

AIM

To investigate the value of machine learning model to predict hypothermia during laparoscopic surgery in patients with multiple trauma.

METHODS

This retrospective study enrolled 220 patients who were admitted with multiple injuries between June 2018 and December 2023. Of these, 154 patients were allocated to a training set and the remaining 66 were allocated to a validation set in a 7:3 ratio. In the training set, 53 cases experienced intraoperative hypothermia and 101 did not. Logistic regression analysis was used to construct a predictive model of intraoperative hypothermia in patients with polytrauma undergoing laparoscopic surgery. The area under the curve (AUC), sensitivity, and specificity were calculated.

RESULTS

Comparison of the hypothermia and non-hypothermia groups found significant differences in sex, age, baseline temperature, intraoperative temperature, duration of anesthesia, duration of surgery, intraoperative fluid infusion, crystalloid infusion, colloid infusion, and pneumoperitoneum volume (P < 0.05). Differences between other characteristics were not significant (P > 0.05). The results of the logistic regression analysis showed that age, baseline temperature, intraoperative temperature, duration of anesthesia, and duration of surgery were independent influencing factors for intraoperative hypothermia during laparoscopic surgery (P < 0.05). Calibration curve analysis showed good consistency between the predicted occurrence of intraoperative hypothermia and the actual occurrence (P > 0.05). The predictive model had AUCs of 0.850 and 0.829 for the training and validation sets, respectively.

CONCLUSION

Machine learning effectively predicted intraoperative hypothermia in polytrauma patients undergoing laparoscopic surgery, which improved surgical safety and patient recovery.

Comparison of Core Body Temperatures in Patients Administered Remimazolam or Propofol during Robotic-Assisted and Laparoscopic Radical Prostatectomy

Background and Objectives: Different types of anesthetics affect thermoregulatory mechanisms, such as the redistribution of body temperature, loss of skin heat, or inhibition of thermoregulatory vasoconstriction. Therefore, we compared remimazolam with propofol in terms of core body temperature in patients undergoing robotic-assisted and laparoscopic radical prostatectomy. Materials and methods: Ninety patients were randomly assigned to either the propofol−remifentanil (PR) group or the remimazolam−remifentanil (RR) group. The PR group (n = 45) received effect-site concentrations of 6.0 μg/mL of propofol and 4 ng/mL of remifentanil, followed by 0.9 mg/kg of 1% rocuronium and maintenance with effect-site concentrations of 2−4 μg/mL of propofol and 3 ng/mL of remifentanil. The RR group (n = 45) received remimazolam 6 mg/kg/h by continuous intravenous infusion and the effect-site concentration of 4 ng/mL of remifentanil, followed by 0.9 mg/kg of 1% rocuronium, remimazolam 1−3 mg/kg/h, and remifentanil 3 ng/mL. The primary outcome was core body temperature, and secondary outcomes included vasoconstriction threshold (°C) and time to onset of vasoconstriction (min). Results: The core body temperature in the RR group was significantly higher at 60, 80, 100, 120, 140, 160, and 180 min after induction than in the PR group (p < 0.01). The vasoconstriction threshold was significantly higher in the RR group (35.2 ± 0.4) than in the PR group (34.8 ± 0.3) (p < 0.01). The time to onset of vasoconstriction was significantly less in the RR group (150.5 ± 10.2) than in the PR group (158.5 ± 8.4) (p < 0.01). However, the incidence of intraoperative hypothermia was not significant between two groups. Conclusions: Remimazolam appears to reduce vasoconstriction threshold less than and had a faster onset of vasoconstriction, resulting in superior thermoregulatory control.

Impact of the Hormonal Status in Women on Intraoperative Hypothermia during Laparoscopic Gynecologic Surgery when Considering the Fresh Gas Flow Rate: A Retrospective Study

Previous studies reported the impact of intrinsic and extrinsic factors on intraoperative hypothermia. However, no clinical study to date has considered the effects of both the phase of the menstrual cycle (an intrinsic factor) and the fresh gas flow rate (FGF) during anesthesia (an extrinsic factor) on the core body temperature and intraoperative hypothermia. This study is aimed at investigatig the effect of the menstrual cycle phase on intraoperative hypothermia when considering the FGF in patients who underwent laparoscopic gynecologic surgery. This study included 667 women aged 19-65 years with menstruation cycles and menopause. The patients were divided into the follicular, luteal, and menopause groups. The primary outcome was the correlations of hormonal status with intraoperative hypothermia. Secondary outcomes included the incidence of intraoperative hypothermia, time to onset of hypothermia, incidence of shivering after anesthesia, and frequency of antishivering drug use in the three groups and risk factors for hypothermia. Overall, the hypothermia incidence was the lowest and the time to onset of hypothermia was the longest in the luteal phase group. At a high FGF, the incidence of hypothermia in the luteal phase group was lower than that in the other two groups (P < 0.05). At a low FGF, the time to onset of hypothermia in the luteal phase group was longer than that in the other two groups (P < 0.05). The female hormonal status had weak positive correlations with hypothermia at low and high FGF rates. A high FGF in univariate and multivariate analyses, follicular phase and menopause in multivariate analysis, and estradiol and progesterone levels in univariate analysis were risk factors for hypothermia. When considering the FGF, the luteal phase is associated with better outcomes concerning intraoperative hypothermia.