AI Based Muscular Ultrasound to Assess Intensive Care Unit-acquired Weakness
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorJena University Hospital
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
Qualifiers
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 design
Treatments tested in this trial
- Neuromuscular Ultrasound
Treatment groups
50 Participants
are divided into 3 treatment groupsSponsors and collaborators
Jena University Hospital
Lead sponsor
University of Rostock
Collaborator
Source ClinicalTrials.gov