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Al Prediction of Sarcopenia Risk in Neurocritical ICU Patients
Sponsor: Trabzon Kanuni Education and Research Hospital
Summary
This prospective observational study aims to evaluate sarcopenia in intensive care patients with intracranial pathologies using ultrasound and to compare the predictive performance of different artificial intelligence models. Rectus femoris muscle thickness will be measured by ultrasound on ICU admission (Day 0) and Day 7. Prealbumin levels will be assessed on Days 0, 3, and 7, and the modified Nutrition Risk in Critically Ill (mNUTRIC) score will be calculated on the first day of ICU admission. Clinical, laboratory, and ultrasonographic data will be integrated into different artificial intelligence models to predict sarcopenia status on Day 7. The study aims to determine the effectiveness of artificial intelligence in the early identification of sarcopenia and to support future clinical decision-making in intensive care practice.
Official title: Artificial Intelligence-Based Prediction of Sarcopenia Risk in Intensive Care Unit Patients With Intracranial Pathology
Key Details
Gender
All
Age Range
18 Years - 65 Years
Study Type
OBSERVATIONAL
Enrollment
100
Start Date
2026-01-01
Completion Date
2026-08-30
Last Updated
2026-07-17
Healthy Volunteers
No
Interventions
Prospective Observational Assessment
Prospective observational assessment including rectus femoris ultrasonography, prealbumin measurements, mNUTRIC scoring, and collection of routine clinical data. No experimental intervention or treatment modification will be performed.
Locations (1)
Trabzon University Faculty of Medicine, Kanuni Training and Research Hospital, Trabzon, 61080
Trabzon, Turkey (Türkiye)