NCT07141420

Application of Large Language Models Techniques to Post-ICU Syndrome Management in Critically Ill Patients: A Fully Longitudinal Mixed Study

• Status: Enrolling By Invitation
• Phase: N/A
• Study type: Interventional
• Enrollment: 90 (estimated)
• Sponsor: The Affiliated Hospital Of Guizhou Medical University · Academic / Other
• Sex: All
• Age: 18 Years – 100 Years
• Healthy volunteers: Not accepted

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.

Conditions

• Post-Intensive Care Syndrome

Interventions

Type	Name	Description
BEHAVIORAL	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.
BEHAVIORAL	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 .
BEHAVIORAL	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 .

Timeline

• Start date: 2025-06-01
• Primary completion: 2026-01-31
• Completion: 2026-02-20
• First posted: 2025-08-26
• Last updated: 2025-08-26

Locations

1 site across 1 country: China