AI could help doctors decide when to take patients off ventilators

NCT ID NCT05886803

First seen Jun 29, 2026 · Last updated Jun 30, 2026 · Updated 1 time

Summary

This study looks at whether machine learning can predict if a patient in intensive care will succeed in a spontaneous breathing test—a key step before removing a ventilator. Researchers will analyze biosignals like heart rate and breathing patterns from 500 patients' medical records. The goal is to develop an algorithm that helps clinicians make safer, faster decisions about weaning patients from mechanical ventilation.

What this could mean

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

Active substance
machine learning algorithm
What this could lead to
If successful, this could give doctors a reliable tool to predict when a patient is ready to breathe on their own, reducing time on ventilators and improving outcomes.
What could go wrong
This is a retrospective study using existing data, so results may not apply to all patients. The algorithm's accuracy in real-time clinical settings remains unproven.

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

Get updates

Get notified about this study

Sign up to get updates when this study changes or when new studies for WEANING FROM MECHANICAL VENTILATION IN CARE UNIT are added.

Our safety recommendation!

By submitting, you agree to our Terms of use

As listed by the trial registrant

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

Contacts and locations

Locations

  • University Hospital of Nice

    RECRUITING

    Nice, 06200, France

More trials for these conditions

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