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Machine Learning-based Longitudinal Study of Post-ICU Syndrome Development Trajectory in Critically Ill Patients and Construction of Clinical Early Warning Models: a Research Protocol for Longitudinal Study

NCT06427265 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 840

Last updated 2025-05-31

No results posted yet for this study

Summary

This project intends to track and evaluate whether post-ICU syndrome will occur 7 days, 1 month, 3 months and 6 months after ICU patients are transferred out of the ICU through a longitudinal study, apply the latent category growth model to identify different trajectory patterns of post-ICU syndrome in critically ill patients, and use modern machine learning models to build an early warning model of the trajectory patterns of post-ICU syndrome.

Conditions

Sponsors & Collaborators

  • Chinese nursing association

    collaborator UNKNOWN

  • The Affiliated Hospital Of Guizhou Medical University

    lead OTHER

Principal Investigators

  • Li Yao · Affiliated Hospital of Guizhou Medical University

Eligibility

Min Age
18 Years
Max Age
100 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2023-12-01
Primary Completion
2025-06-01
Completion
2026-06-01

Countries

  • China

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 NCT06427265 on ClinicalTrials.gov