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

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.

"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 ."

"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 ."