Not Yet RecruitingNot Applicable

Using Artificial Intelligence Models for Predicting The Need for Intubation and Successful Weaning From Mechanical Ventilation in ICU Patients

600 participantsStarted 2025-10-01

Plain-language summary

Using artificial intelligence (AI) approach to build a model to determine the optimal timing of intubation and optimal timing of weaning from MV for ICU patients, and compare outcomes with these which depend on clinicians dicision. And also assess whether AI-assisted decisions improve patient outcomes (e.g., reduced intubation delays, shorter ventilation duration).

Who can participate

Age range18 Years – 90 Years

SexALL

See this in plain English?

AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion Criteria * Adult patients (≥18 years) in ICUs at risk of respiratory failure. * Adults (≥18 years) receiving mechanical ventilation for \>24 hours and deemed ready for weaning. Exclusion Criteria: * \- Patients with a pre-existing "Do Not Intubate" (DNI) order. * \- Patients with irreversible neurological conditions affecting weaning

What they're measuring

Perfect time to intubate and to Wean

Timeframe: 2 years

Trial details

NCT IDNCT07065838

SponsorAssiut University

Sponsor typeOTHER

Study typeOBSERVATIONAL

Primary completion2027-11-01

View on ClinicalTrials.gov More Respiratory Distress Syndrome (RDS) trials