About this trial
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 criteria
This trial accepts healthy volunteersQualifiers
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)
Disqualifiers
No informed consent
Emergency surgery
Previous participation in the same study
Preexisting neuromuscular disease
Trial population
All patients with critical illness fulfilling the inclusion criteria should be screened for the study on two surgical ICUs at the department of anesthesiology and intensive care medicine of Jena University Hospital, Germany.
Trial design
Case-control
Prospective
Treatments tested in this trial
Neuromuscular Ultrasound
Diagnostic testNon-invasive ultrasound of peripheral muscles of the upper and lower extremities with additional artificiall intelligence processing of ultrasound images.
Treatment groups
Trial outcomes
Primary outcomes
Incidence of abnormalities of muscle echogenicity assesed by muscular ultrasound
Determination of the number of patients correctly classified as ICUAW (+) using AI-based ultrasound evaluation
Secondary outcomes
Incidence of ICUAW severity assessed by Heckmatt Scale
Incidence of ICUAW severity assessed by Medical Research Council Sum Score
Days on ventilation
Days on vasopressors
Sponsors and contacts
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Jena University Hospital
Lead sponsor
University of Rostock
Collaborator