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Development and Comparison of a Machine Learning-Based Risk Prediction Model for Delayed Extubation After General Anesthesia

Development and Comparison of a Machine Learning-Based Risk Prediction Model for Delayed Extubation After General Anesthesia

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400090247
Enrollment
Unknown
Registered
2024-09-26
Start date
2024-09-30
Completion date
Unknown
Last updated
2024-09-30

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

Conditions

delayed extubation

Interventions

Sponsors

Shenshan Medical Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
0.1 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1.Select patients who were admitted to the Post-Anesthesia Care Unit (PACU) at the Sun Yat-sen Memorial Hospital, Shenshan Center of Sun Yat-sen University, from September 2023 to May 2024. 2.The anesthesia method used was endotracheal intubation general anesthesia. 3.The patients were aged between 1 month and 90 years.

Exclusion criteria

Exclusion criteria: 1.The patient was comatose preoperatively and had severe mental illness or psychiatric disorders. 2.The endotracheal tube was removed before the patient was transferred to the recovery room. 3.Missing data exceeds 30% of the total collected items.

Design outcomes

Primary

MeasureTime frame
Delayed Extubation;

Secondary

MeasureTime frame
temperature;Venous blood sample test results;Basic demographic information;Intraoperative fluid balance;

Countries

China

Contacts

Public ContactLuojianwei

Shenshan Medical Center,Memoral Hospital Of Sun-Sen University

363256833@qq.com+86 159 8918 5387

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026