Researchers Develop MND Feeding-Tube Predictor Tool
A team led by the University of Sheffield has developed an AI model that predicts when people with Motor Neurone Disease will need a feeding tube, using routine diagnostic measurements and data from over 20,000 patients. Published in eBioMedicine, the model estimates the optimal gastrostomy window with a median error of 3.7 months at diagnosis and 2.6 months after six months. Researchers plan a prospective clinical trial to validate the tool.
Key Points
- 1Predicts optimal gastrostomy timing within median error 3.7 months using diagnosis-time routine measurements
- 2Leverages data from over 20,000 MND patients to address unpredictable disease progression and timing
- 3Enables clinicians to plan gastrostomy proactively, improving nutrition, quality of life, and potential survival
Scoring Rationale
Strong clinical dataset and peer-reviewed publication, but limited immediate deployment pending prospective trial validation and broader external testing.
Sources
Public references used for this report.
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