Predicting Hypothermia in Gynecological Laparoscopic Surgery Using Machine Learning

NCT07353528 | Not Yet Recruiting

• 1 other identifier: 202501
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 4

Brief Summary

Brief Title: Predicting Hypothermia in Gynecological Laparoscopic Surgery Using Machine Learning Brief Summary: This study aims to develop and validate a machine learning model for predicting intraoperative hypothermia (IOH) in patients undergoing gynecological laparoscopic surgery based on preoperative clinical indicators. This prospective, multicenter case-control study will enroll female patients aged 18 years and older who are scheduled for laparoscopic surgery across multiple hospitals from 2026 to 2027. The primary objective is to identify high-risk patients who may experience IOH, defined as a core temperature below 36.0°C during surgery. Participants will be classified into two groups: the IOH group, consisting of patients who experience hypothermia, and the normal temperature group, comprising patients who maintain a core temperature of 36.0°C or higher. Data collection will include demographics, comorbidities, surgical details, anesthesia information, and preoperative laboratory results. The primary outcome measure will be the area under the curve (AUC) of the model, assessing its predictive performance at various thresholds. Secondary outcomes will include sensitivity, positive predictive value, negative predictive value, and F1 score. The study hypothesizes that the developed machine learning model will significantly improve the accuracy and timeliness of predicting IOH, thereby enhancing patient safety during surgery and postoperative recovery. This research is expected to inform clinical practices related to preventative warming strategies, ultimately improving patient outcomes in gynecological laparoscopic surgery.

Conditions

Laparoscopic Surgery; Intraoperative Hypothermia; Gynecological Surgery

Keywords

Laparoscopic surgery; Intraoperative hypothermia; Machine learning; Gynecology

Outcome Measures

Primary Outcomes (1)

• Area Under the Receiver Operating Characteristic Curve (AUC) of the machine learning model for predicting intraoperative hypothermia

  The primary outcome is the discriminatory performance of the developed machine learning model for predicting the occurrence of intraoperative hypothermia (defined as a core temperature \< 36.0°C), as measured by the Area Under the Receiver Operating Characteristic Curve (AUC) evaluated on the independent testing set.

  During surgery

Secondary Outcomes (4)

• Sensitivity

  During surgery

• Positive Predictive Value

  During surgery

• Negative Predictive Value

  During surgery

• F1-Score

  During surgery

Study Arms (2)

Hypothermia Group

This cohort consists of patients who develop intraoperative hypothermia (IOH) during gynecological laparoscopic surgery. IOH is defined as a core body temperature (measured by a wireless temperature monitoring system) falling below 36.0°C at any time during the surgery.

Normothermia Group

This cohort comprises patients whose core body temperature (measured by a wireless temperature monitoring system) remains at or above 36.0°C throughout the entire gynecological laparoscopic surgery, and who do not develop intraoperative hypothermia (IOH). These patients serve as the control group for this study.

Eligibility Criteria

• Age: 18 Years+
• Gender Eligibility Details: eligibility is based on biological sex (female) as it pertains to the anatomical structures involved in the surgical procedure, not on gender identity.
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population consists of adult female patients undergoing gynecological laparoscopic surgery at multiple collaborating hospitals (including Chengdu Jinjiang District Maternal and Child Health Hospital, etc.). All participants must meet the inclusion criteria and not meet any exclusion criteria. Based on whether their intraoperative core temperature (measured by a wireless temperature monitoring system) falls below 36.0°C, patients will be categorized into either the "Hypothermia Group" (case) or the "Normothermia Group" (control). This is a prospective case-control study.

You may qualify if:

• Female patients aged 18 years or older.
• Patients scheduled for laparoscopic surgery.

You may not qualify if:

• Preoperative body temperature exceeding 37.5°C or below 36.0°C.
• History of hypothyroidism or hyperthyroidism.
• Patients with thermoregulatory dysfunction, such as severe infection or central nervous system disorders.
• Patients who refuse to sign the informed consent form.

Sponsors & Collaborators

• Sichuan Jinxin Xinan Women & Children's Hospital: collaborator
• People ' s Hospital of Dayi County: collaborator
• Medical Center Hospital of QiongLai City: collaborator
• Chengdu Jinjiang Maternity and Child Health Hospital: lead

Study Sites (4)

Chengdu Jinjiang District Women & Children Health Hospital

Chengdu, Sichuan, 610011, China

Location

Sichuan Jinxin Xinan Women & Children's Hospital

Chengdu, Sichuan, 610011, China

Location

People ' s Hospital of Dayi County

Chengdu, Sichuan, 611300, China

Location

Medical Center Hospital of QiongLai City

Chengdu, Sichuan, 611532, China

Location

Related Publications (10)

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  PMID: 32011262 BACKGROUND

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• Cao B, Li Y, Liu Y, Chen X, Liu Y, Li Y, Wu Q, Ji F, Shu H. A multi-center study to predict the risk of intraoperative hypothermia in gynecological surgery patients using preoperative variables. Gynecol Oncol. 2024 Jun;185:156-164. doi: 10.1016/j.ygyno.2024.02.009. Epub 2024 Feb 29.

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  PMID: 37878246 BACKGROUND

Central Study Contacts

Bo Liu, MS

CONTACT

+8618502846036; liubojjfy@163.com

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Director of Anesthesiology Department

Study Record Dates

• First Submitted: November 28, 2025
• First Posted: January 20, 2026
• Study Start: March 1, 2026
• Primary Completion: March 1, 2026
• Study Completion (Estimated): July 1, 2026
• Last Updated: January 20, 2026

Record last verified: 2026-01

Data Sharing

• IPD Sharing: Will share

Locations

CN (4)