Can a simple score predict who survives a bad fall?
NCT ID NCT07158554
First seen Oct 31, 2025 · Last updated Jun 22, 2026 · Updated 31 times
Summary
One in three adults over 65 falls each year, and many lie on the floor for over an hour, which can cause muscle breakdown and kidney damage. This study will look at medical records from 1,000 older adults to create a risk prediction model that helps emergency doctors quickly decide who needs hospital treatment and who can safely go home. The goal is to reduce unnecessary hospital stays while catching serious complications early.
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This is a summary of
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Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
This is a summary of the original study . Summaries may miss details or leave out important information. Before applying or accepting participation, make sure you have read and understood the full study. Curemydisease.com takes no responsibility whatsoever for anything missed, misunderstood, or acted upon as a result of our summary — we know it does not capture everything.
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Contacts and locations
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Study contacts
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Contact
Phone: •••-•••-•••• Email: •••••@•••••
Locations
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Southend University Hospital
Westcliff-on-Sea, Essex, SS0 0RY, United Kingdom
Contact Phone: •••-•••-•••• Email: •••••@•••••
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What this could mean
Our plain-language read of the trial. This is informational only — not medical advice or a prediction.
What this could lead to
If successful, this could give emergency doctors a simple tool to quickly decide which older fall patients need hospital care and which can safely go home.
What could go wrong
This is an observational study that only builds a prediction model, not a treatment. The model may not work well in other hospitals or for all patients.
Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.