AI-guided determination of optimal PEEP
Official title: Evaluation of the Success of Artificial Intelligence Models in Determining the Optimal Positive End-Expiratory Pressure (PEEP) in Mechanical Ventilation in Intensive Care
Run by Kanuni Sultan Suleyman Training and Research Hospital · NCT06844916 · Data updated 2026-11-12
This will test whether AI can recommend the best PEEP settings for adults on mechanical ventilation in the ICU.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 145 (estimated) |
| Sponsor | Kanuni Sultan Suleyman Training and Research Hospital Academic / other |
| Locations | 1 site (Istanbul) |
| Status | Recruiting |
| Started | March 1, 2025 |
| Main results expected | February 1, 2026 |
| Study ends | February 2, 2026 |
| Registry record updated | June 4, 2025 |
| Trial ID | NCT06844916 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults (≥18 years) in the ICU who are hemodynamically stable, require mechanical ventilation, have complete ventilation and arterial blood gas records, and whose legal representatives provide informed consent are eligible.
✕Probably not a fit
Patients on ECMO, those with severe hemodynamic instability requiring continuous vasopressors, or patients with incomplete medical records are excluded and unlikely to benefit from this approach.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This is a prospective observational study enrolling adults in the ICU who are hemodynamically stable and require mechanical ventilation. Respiratory mechanics will be measured using inspiratory and expiratory hold maneuvers to capture compliance, elastance, auto-PEEP, and time constants, and pressure–volume curves will be analyzed for lower and upper inflection points. AI models will generate PEEP recommendations which will be compared to PEEP levels set manually by ICU specialists following standardized titration protocols. Clinicians retain final control of ventilator settings while the study collects parallel AI and expert data for comparison.
Why it matters
Potential benefit: If successful, AI-generated PEEP recommendations could help personalize ventilator settings to improve oxygenation and reduce ventilator-induced lung injury.
How similar studies have gone: Prior retrospective and pilot studies have suggested AI can aid ventilator setting decisions, but prospective comparisons against expert titration remain limited.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Patients aged 18 years or older (adult patient group). * Patients requiring mechanical ventilation in the intensive care unit (ICU). * Hemodynamically stable patients with stable blood pressure and heart rate. * Patients with complete medical records, including arterial blood gas values and ventilation parameters. * Patients whose legal representatives (if applicable) have provided informed consent for study participation. Exclusion Criteria: * Patients receiving extracorporeal membrane oxygenation (ECMO). * Patients with severe hemodynamic instability, such as refractory hypotension or arrhythmias requiring continuous vasopressor support. * Patients with incomplete medical records, particularly those missing critical data on ventilation parameters or arterial blood gas analysis. * Patients or their legal representatives who decline participation in the study.
Where it's running
-
Health Science University İstanbul Kanuni Sultan Süleyman Education and Training Hospital
Istanbul, Turkey (Türkiye) Recruiting
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.