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AI could predict the perfect moment to take ICU patients off ventilators

NCT ID NCT07658131

Knowledge-focused Sponsor: Taichung Veterans General 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
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 Results may not be published yet.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This status has not been confirmed recently, so it may be out of date.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 tests an artificial intelligence program designed to predict the best time to remove a breathing tube (extubation) from patients in intensive care. Researchers will use data from 1500 adults who were on a ventilator for at least 72 hours across four hospitals. The AI analyzes routine clinical information like ventilator settings and vital signs to forecast successful extubation. The goal is to see how accurately the tool performs compared to standard medical judgment.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

Active substance
AI-aided weaning software
What this could lead to
If successful, this AI tool could help doctors decide when to safely remove a breathing tube, potentially reducing time on ventilators and improving outcomes for critically ill patients.
What could go wrong
This is a retrospective study using existing data, not a live trial. The AI may not perform as well in real-world settings or on different patient populations.

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

1,500 people

The number who actually took part.

Started

Jan 2020

Finished

Dec 2024

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

Adult patients with acute respiratory failure who were admitted to participating hospitals between January 2022 and December 2024 and required invasive mechanical ventilation for at least 24 hours. This is a retrospective study using existing clinical and imaging data for model validation.

Ages

20 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: * Adult patients aged 20 years or older. * Admitted to the intensive care unit (ICU) at one of the participating hospitals between January 1, 2020 and December 31, 2024. * Received invasive mechanical ventilation for at least 72 hours. * Availability of de-identified clinical data required for model validation. Exclusion Criteria: * Patients who did not receive invasive mechanical ventilation. * Duration of mechanical ventilation less than 72 hours. * Missing key clinical variables required for model validation.

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Conditions

The condition(s) this trial relates to.

Critical Illness respiratory failure

As listed by the trial registrant

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

Critical illness Mechanical ventilation Respiratory failure

Contacts and locations

Locations

  • Taichung Veterans General Hospital

    Taichung, Taiwan

More trials for these conditions

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