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 | Recruiting

• 3 other identifiers: ZHKYQ202316No. ZHKYQ202316No. Gyfynsfc[2023]35
• Study Type: observational
• Target: 840
• Locations: 1 country
• Sites: 1

Brief 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

Intensive Care Unit Syndrome; Prediction; Cognitive Impairment; Sleep Disorder; Memory Disorders

Keywords

Post-icu syndrome; Prediction model; Development Trajectory

Outcome Measures

Primary Outcomes (1)

• Correlation scale score

  Patient: 1. Post-icu syndrome assessment of ICU survivors: Healthy Aging Brain Care monitoring(HABC Monitor) score; 2. ICU related Memory: Intensive Care Unit Memory Tool (ICUMT); 3. Sleep quality: Richards-Campbell Sleep Questionnaire (RCSQ); 4. Perceived Social Support Scale (PSSS). Family members: 1. Sleep quality of family members: Richards-Campbell Sleep Questionnaire (RCSQ); 2. anxiety and Depression of family members: Hospital anxiety and Depression Scale score; 3. Family fatigue: Scores of fatigue rating Scale; 4. PTSD of family members: Event Impact Scale score;

  2024-2026

Eligibility Criteria

• Age: 18 Years - 100 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Stage one involved studying patients discharged from the ICU and their families to investigate the occurrence and factors influencing post-intensive care syndrome (PICS), identifying various developmental patterns of PICS. A minimum sample size of 840 patients and 420 family members was established. Stage two focused on developing and evaluating a machine learning-based early warning model for PICS. The model construction utilized data from stage one, while the evaluation included 525 patients and 393 family members who met the exclusion criteria.

You may qualify if:

• Length of stay in ICU ≥24h;
• Age ≥18 years old;
• Conscious when leaving ICU, communicating with investigators without barriers;
• Informed consent. Family members：
• One family member ≥18 years of age was selected for each patient;
• Assume the main role of caring for patients and medical decision-making;
• No history of mental illness or other serious organic diseases;
• Informed consent and voluntary participation in this study.

You may not qualify if:

• Have been in ICU for more than 24h within 3 months before this admission;
• Transferred to another ICU;
• Cognitive impairment existed before ICU admission (BDRS \> 4 points);
• Severe hearing impairment, dysarthria, etc., which cannot be followed up;
• Unable to complete the questionnaire survey due to serious illness.
• Family members:
• Family members refuse to participate in the study due to their own reasons;
• Severe hearing and language impairment, unable to cooperate with researchers.

Sponsors & Collaborators

• The Affiliated Hospital Of Guizhou Medical University: lead
• Chinese nursing association: collaborator

Study Sites (1)

Affiliated Hospital of Guizhou Medical University

Guiyang, Guizhou, 550004, China

RECRUITING

MeSH Terms

Conditions

Cognitive Dysfunction; Sleep Wake Disorders; Memory Disorders

Condition Hierarchy (Ancestors)

Cognition Disorders; Neurocognitive Disorders; Mental Disorders; Nervous System Diseases; Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Neurobehavioral Manifestations

Study Officials

• Li Yao

  Affiliated Hospital of Guizhou Medical University

  STUDY CHAIR

Central Study Contacts

Tingrui WANG

CONTACT

19117899885; W19117899885@163.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 19, 2024
• First Posted: May 23, 2024
• Study Start: December 1, 2023
• Primary Completion: June 1, 2025
• Study Completion (Estimated): June 1, 2026
• Last Updated: May 31, 2025

Record last verified: 2024-06

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)