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
Trial Parameters
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.
Eligibility Criteria
Inclusion Criteria patients : * 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. Exclusion Criteria patients : * 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.