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AI could help seniors leave the hospital sooner

NCT ID NCT04965480

Knowledge-focused Sponsor: Centre Hospitalier Universitaire, Amiens Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed This study
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jun 27, 2026 · Last updated Jun 27, 2026

Summary

This study tested whether a computer program could predict which older patients (over 75) would have unnecessary days in the hospital. Researchers analyzed electronic health records from 102 patients in an acute geriatric unit. The goal was to create an algorithm that flags when a patient is likely to be stuck waiting for a transfer to a rehab facility, so hospitals can act faster.

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 algorithm could help hospitals identify which older patients are likely to have delayed discharge, allowing for better planning and shorter hospital stays.
What could go wrong
This is a small, completed study that developed an algorithm, not a treatment. The algorithm may not work as well in other hospitals or with different patient groups.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

102 people

The number who actually took part.

Started

Aug 2021

Finished

Apr 2022

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

Patients aged \>75 years, hospitalized in AGU in Amiens University Hopsital

Ages

75 years and older

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * age : \>75 years * patient hospitalized in an AGU Exclusion Criteria: * refusal to participate

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Conditions

The condition(s) this trial relates to.

Language language disorder specific language impairment

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Electronic health record Geriatric Language OLDER

Contacts and locations

Locations

  • CHU Amiens Picardie

    Amiens, Picardie, 80054, France

More trials for these conditions

Other studies related to the condition(s) this trial covers.