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AI could predict patient crashes before they happen

NCT ID NCT06574906

Knowledge-focused Sponsor: Kepler University Hospital 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 This study
Running, but no longer taking on new participants.
Completed
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 26, 2026 · Last updated Jun 26, 2026

Summary

This study tests whether machine learning can predict changes in early warning scores—vital signs that show if a patient is getting worse—in general hospital wards. Researchers will analyze data from 3,000 patients to see if AI can spot trouble earlier than current spot-check methods. The goal is to give nurses and doctors a heads-up before a patient's condition becomes critical.

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 lead to an AI system that alerts hospital staff to patient deterioration before it becomes life-threatening, potentially saving lives.
What could go wrong
This is an observational study using existing data, so it won't directly test a treatment. The AI predictions may not work perfectly in real-world settings or for all patients.

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

About 3,000 people

The number the study aims to enrol. It can still change while the study runs.

Started

Aug 2025

Expected to finish

Oct 2026

An estimate. End dates often move.

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 treated in general wards.

Ages

18 years and older

Sex

Anyone

Healthy volunteers

Accepted

You do not need to have the condition being studied to take part.

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: * Treated in general ward between 2024-10-01 and 2026-10-31 at the study center. Exclusion Criteria: * None.

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As listed by the trial registrant

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

Patient safety

Contacts and locations

Locations

  • Johannes Kepler University, Kepler University Hospital

    Linz, Upper Austria, 4020, Austria

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