Predicting ICU-Acquired Sarcopenia in Intracranial Pathology: Turkish Trial Evaluates AI Models Against Ultrasound Muscle Metrics
247 Health News Editorial
·18 July 2026
·4 min read
·clinical-trialsA prospective observational trial at Trabzon Kanuni Education and Research Hospital is evaluating whether AI models can predict ICU-acquired sarcopenia by Day 7 in patients admitted with acute intracranial pathologies including stroke, haemorrhage, and brain tumours. The study integrates serial rectus femoris ultrasound, prealbumin levels, and mNUTRIC scoring to train and compare multiple AI architectures. Findings could inform early nutritional and rehabilitative decision-making in one of critical care's most functionally vulnerable patient groups.
Originally reported by ClinicalTrials.gov
References
- 1.Trabzon Kanuni Education and Research Hospital. (2025). Artificial intelligence-based prediction of sarcopenia risk in intensive care unit patients with intracranial pathology (NCT07712198). ClinicalTrials.gov. https://clinicaltrials.gov/study/NCT07712198
- 2.Wieske, L., Dettling-Ihnenfeldt, D. S., Verhamme, C., Nollet, F., van Schaik, I. N., Schultz, M. J., Horn, J., & van der Schaaf, M. (2015). Impact of ICU-acquired weakness on post-ICU physical functioning: A follow-up study. Critical Care, 19(1), 196. https://doi.org/10.1186/s13054-015-0937-4
- 3.Puthucheary, Z. A., Rawal, J., McPhail, M., Connolly, B., Ratnayake, G., Chan, P., Hopkinson, N. S., Phadke, R., Dew, T., Sidhu, P. S., Velloso, C., Seymour, J., Agley, C. C., Selby, A., Limb, M., Edwards, L. M., Smith, K., Rowlerson, A., Rennie, M. J., … Montgomery, H. E. (2013). Acute skeletal muscle wasting in critical illness. JAMA, 310(15), 1591–1600. https://doi.org/10.1001/jama.2013.278481
- 4.Singer, P., Blaser, A. R., Berger, M. M., Alhazzani, W., Calder, P. C., Casaer, M. P., Hiesmayr, M., Mayer, K., Montejo, J. C., Pichard, C., Preiser, J. C., van Zanten, A. R. H., Oczkowski, S., Szczeklik, W., & Bischoff, S. C. (2019). ESPEN guideline on clinical nutrition in the intensive care unit. Clinical Nutrition, 38(1), 48–79. https://doi.org/10.1016/j.clnu.2018.08.037
- 5.Rahman, A., Hasan, R. M., Agarwala, R., Martin, C., Day, A. G., & Heyland, D. K. (2016). Identifying critically-ill patients who will benefit most from nutritional therapy: Further validation of the 'modified NUTRIC' nutritional risk assessment tool. Clinical Nutrition, 35(1), 158–162. https://doi.org/10.1016/j.clnu.2015.02.015
- 6.Hadda, V., Khan, M. A., Khilnani, G. C., Guleria, R., Madan, K., Mohan, A., & Bhatt, S. P. (2021). Bedside ultrasound assessment of rectus femoris muscle thickness in critically ill patients: A systematic review and meta-analysis. Journal of Intensive Care Medicine, 36(1), 45–54. https://doi.org/10.1177/0885066619887699
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247 Health News Editorial
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