AI Based Muscular Ultrasound to Assess Intensive Care Unit-acquired Weakness
Artificial IntelligenCe Based UlTrasonographic Assessment of IntensiVe CAre UniT-acquired WEakness (ACTIVATE)
Jena University Hospital
50 participants
Oct 1, 2024
OBSERVATIONAL
Conditions
Summary
The aim of this observational case-control study is to investigate, whether artificial intelligence can detect ultrasound-derived imaging characteristics typical for intensive care unit-acquired weakness. The main questions it aims to answer are: 1. Is the evaluation of specific parameters of neuromuscular ultrasound using AI-based image analysis suitable for detecting and monitoring critically ill ICU patients with ICUAW? 2. Do the results of AI-based ultrasound image analysis correlate with: (A) the severity of ICUAW (B) the visual grading of muscle echogenicity (C) the 30- and 90-day-outcome?
Eligibility
Inclusion Criteria4
- Patients aged 18 years or above
- Major elective surgery, e.g. cardiothoracic or abdominal surgery
- Expected ICU stay >1 day postoperatively
- Healthy, age-machted subjects without ICUAW (recruited from staff of the department of anesthesiology and intensive care medicine)
Exclusion Criteria6
- No informed consent
- Emergency surgery
- Previous participation in the same study
- Preexisting neuromuscular disease
- Preexisting central nervous system disease with residual neuromuscular impairment (e.g. cerebral haemorrhage, stroke, brain tumor)
- High-dose glucocorticoid therapy (>300 mg hydrocortisone or equivalent per day) before or during particiation in the study
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Interventions
Non-invasive ultrasound of peripheral muscles of the upper and lower extremities with additional artificiall intelligence processing of ultrasound images.
Locations(1)
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NCT06765551