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Research on constructing a dynamic prediction model of intraoperative hypothermia risk based on machine learning and an intelligent early warning system

Research on constructing a dynamic prediction model of intraoperative hypothermia risk based on machine learning and an intelligent early warning system

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600125161
Enrollment
Unknown
Registered
2026-05-21
Start date
2026-05-21
Completion date
Unknown
Last updated
2026-05-25

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Intraoperative Hypothermia

Interventions

Patients undergoing general anesthesia at a tertiary hospital in Zhuhai, China:none

Sponsors

Fifth Affiliated Hospital, Sun Yat-Sen University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. ASA physical status classification grade ?–?; 2. Duration of anesthesia > 1 hour; 3. Patients undergoing general anesthesia at The Fifth Affiliated Hospital of Sun Yat-sen University between January and December 2025; 4. Postoperative recovery in the Post-Anesthesia Care Unit (PACU).

Exclusion criteria

Exclusion criteria: 1. Pre-induction core body temperature > 37.5? or < 36.0?; 2. Pregnant or lactating patients; 3. Patients receiving special intraoperative temperature management (e.g., cardiac surgery requiring cardiopulmonary bypass); 3. Patients with incomplete clinical data.

Design outcomes

Primary

MeasureTime frame
Intraoperative hypothermia incidence rate;Area under the ROC curve;—

Secondary

MeasureTime frame
Anesthesia recovery time;Postoperative shivering;—

Countries

China

Contacts

Public ContactLi Qiaomin

The Fifth Affiliated Hospital of Sun Yat-sen University

liqiaomin@tom.com+86 756 2528354

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: May 30, 2026