Predictive Algorithms for Critical Rehabilitation Outcomes

Recruiting now

Conditions studied: Intensive Care, Mechanical Ventilation, Rehabilitation, Algorithms

In brief

An increasing amount of evidence from evidence-based medicine indicates that early rehabilitation intervention for patients receiving mechanical ventilation is safe and feasible, and can promote functional recovery and reduce hospital stay. However, the conscious state, respiratory function, and daily living activities of these patients after being discharged from the ICU vary greatly, and some patients do not show obvious benefits. How to identify which patients may have benefit from early rehabilitation is a key issue that needs to be addressed in critical care rehabilitation. This study aims to investigate the clinical data related to the disease of the ICU survivors who received mechanical ventilation as the research object, by collecting their clinical data when receiving early rehabilitation intervention, and constructing a clinical prediction model for the efficacy of early rehabilitation intervention in the ICU through the selection of optimal regression equation or machine learning algorithm. The application of this model can effectively determine whether ICU inpatients need early rehabilitation intervention, thereby reducing complication rates and improving their quality of life.

Key facts

Study ID
NCT06532994
Run by
Wuhan University
People needed
250
Starts
2024-08-01
Expected to finish
2026-12-30
Last updated by the study team
2026-04-21

Who can join

Age: 18 and older, up to 90. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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