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AI could help ventilator patients breathe easier by timing suction better

NCT ID NCT07375667

First seen Feb 01, 2026 · Last updated Jun 23, 2026 · Updated 21 times

Summary

This study tests whether monitoring changes in airway resistance can help doctors decide the best time to suction mucus from the lungs of patients on ventilators. Researchers will use machine learning to analyze data from 258 patients with conditions like ARDS or severe pneumonia. The goal is to improve suction timing, reduce lung inflammation, and potentially lower the risk of ventilator-associated pneumonia.

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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

Study contacts

  • Contact

    Phone: •••-•••-•••• Email: •••••@•••••

  • Contact

    Phone: •••-•••-•••• Email: •••••@•••••

Locations

  • Peking Union Medical College Hospital

    RECRUITING

    Beijing, Beijing Municipality, 100000, China

    Contact Phone: •••-•••-•••• Email: •••••@•••••

  • The First Affiliated Hospital of Bengbu Medical University

    RECRUITING

    Bengbu, Anhui, 233000, China

    Contact Phone: •••-•••-•••• Email: •••••@•••••

  • the Second Affiliated Hospital of Zhejiang University School of Medicine

    RECRUITING

    Hangzhou, Zhejiang, 310009, China

    Contact Phone: •••-•••-•••• Email: •••••@•••••

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 provide a more precise, data-driven way to decide when to suction ventilated patients, potentially reducing lung infections and improving outcomes.

What could go wrong

This is an early-stage observational study, not a treatment trial. The findings may not translate into routine practice, and machine learning models can be limited by data quality.

Conditions

The condition(s) this trial relates to.

acute respiratory distress syndrome neonatal respiratory failure pneumonia Pneumonia, Ventilator-Associated

As listed by the trial registrant

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