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Development and Validation of an Interpretable Machine Learning Model for Predicting Venous Thromboembolism（VTE）in Intensive Care Unit (ICU) Patients

NCT07596264 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 12061

Last updated 2026-05-19

No results posted yet for this study

Summary

Venous thromboembolism remains a leading cause of preventable mortality in intensive care unit (ICU) patients. Existing risk-stratification tools were developed in general medical populations and lack ICU-specific predictors. This study was to develop and validate an interpretable machine learning (ML) model to predict VTE in ICU patients.

Conditions

Interventions

OTHER

no intervention

no intervention

Sponsors & Collaborators

  • Beijing Tsinghua Chang Gung Hospital

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-01-01
Primary Completion
2025-12-31
Completion
2025-12-31

Countries

  • China

Study Locations

More Related Trials

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 NCT07596264 on ClinicalTrials.gov