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External Validation of AI-Aided Weaning Software Using Multicenter Retrospective Data

NCT07658131 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 1500

Last updated 2026-06-22

No results posted yet for this study

Summary

This multicenter retrospective study aims to externally validate an artificial intelligence-aided weaning software developed using intensive care unit data from Taichung Veterans General Hospital between 2015 and 2019. The model predicts the optimal timing for extubation using routinely collected clinical variables including ventilator parameters, physiologic measurements, and fluid and nutrition information. De-identified data from four hospitals collected between 2020 and 2024 will be used to evaluate model performance. Performance metrics include sensitivity, specificity, accuracy, area under the receiver operating characteristic curve (AUROC), and F1 score.

Conditions

Sponsors & Collaborators

  • Mackay Memorial Hospital

    collaborator OTHER

  • Kaohsiung Medical University Chung-Ho Memorial Hospital

    collaborator OTHER

  • Tungs' Taichung Metroharbor Hospital

    collaborator UNKNOWN

  • Taichung Veterans General Hospital

    lead OTHER

Eligibility

Min Age
20 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-01-01
Primary Completion
2024-12-31
Completion
2024-12-31

Countries

  • Taiwan

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07658131 on ClinicalTrials.gov