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Application of Large Language Models Techniques to Post-ICU Syndrome Management in Critically Ill Patients: A Fully Longitudinal Mixed Study
Sponsor: The Affiliated Hospital Of Guizhou Medical University
Summary
The goal of this clinical trial is to evaluate whether Large Language Models (LLMs) combined with an optimized care program can effectively manage Post-Intensive Care Syndrome (PICS) in adult ICU survivors (aged ≥18 years) discharged from a tertiary hospital in China. The main questions it aims to answer are: * Does the intervention (optimized program + LLMs) improve physical, psychological, cognitive, and social function recovery compared to standard care or the optimized program alone? * How do patients experience and perceive the utility of LLMs in PICS self-management during recovery? Researchers will compare three groups: 1. Group A (routine care) 2. Group B (optimized program without LLMs) 3. Group C (optimized program + LLMs) to see if adding LLMs significantly enhances PICS symptom management, patient self-efficacy, and quality of life over 6 months post-discharge. Participants will: * Install and use the Kimi Smart Assistant LLM (Group C only) for health queries under nurse supervision. * Complete standardized questionnaires at discharge (baseline), 7 days, 1 month, 3 months, and 6 months post-discharge: * PICS Symptom Questionnaire (PICSQ) * Pittsburgh Sleep Quality Index (PSQI) * Anxiety (GAD-7) and Depression (PHQ-9) scales * Self-Management Ability Scale (AHSMSRS) * Attend semi-structured interviews (Group C only) at 3 and 6 months to share experiences with LLM use.
Key Details
Gender
All
Age Range
18 Years - 100 Years
Study Type
INTERVENTIONAL
Enrollment
90
Start Date
2025-06-01
Completion Date
2026-02-20
Last Updated
2025-08-26
Healthy Volunteers
No
Conditions
Interventions
Routine Care
Participants receive standard post-ICU follow-up care according to hospital protocols . This includes routine health assessments and general rehabilitation guidance at designated intervals (discharge, 1/3/6 months post-discharge). No structured PICS management program or AI technology is provided.
Health Promotion Model-Based Optimized Program
An evidence-based, multidisciplinary rehabilitation protocol for Post-Intensive Care Syndrome (PICS) management, developed using the Health Promotion Model (HPM). It includes: Personalized rehabilitation plans addressing physical, cognitive, and psychological recovery. Structured follow-up at discharge, 1/3/6 months post-discharge. Components: Physical function training, cognitive exercises, anxiety/depression coping strategies, and sleep hygiene education. Delivery: Clinician-guided (no AI/technology involved). Developed via literature review and validated by ICU physicians and nursing experts .
LLM-Enhanced Optimized Program
Combines the HPM-Based Optimized Program with Large Language Model (LLM) technology for dynamic personalization: AI-generated rehabilitation plans: ChatGPT-4 synthesizes patient data (baseline + follow-ups) to create/update monthly plans, reviewed by a multidisciplinary expert team. Patient-facing LLM tool: "Kimi Smart Assistant" installed for daily health queries under strict safety protocols (all outputs validated by nurses via WeChat). Phased implementation: Pre-discharge: LLM training + baseline plan generation. 1/3/6 months: Plan updates + outcome tracking. 3/6 months: Semi-structured interviews on LLM experience. Includes LLM usage guidelines and expert validation safeguards .
Locations (1)
The Affiliated Hospital of Guizhou Medical University
Guiyang, Guizhou, China