Using artificial intelligence to improve mechanical ventilation decisions
Retrospective Use of Patient Treatment Data for the Evaluation and Further Development of an Artificial Intelligence-based Algorithm for Clinical Decision Support in Invasive Mechanical Ventilation of Intensive Care Patients
Technische Universität Dresden · NCT05668637
This study tests whether an artificial intelligence tool can help doctors make better decisions about ventilator settings for patients on mechanical ventilation in the ICU.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 318542 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Technische Universität Dresden (other) |
| Locations | 8 sites (Cleveland, Ohio and 7 other locations) |
| Trial ID | NCT05668637 on ClinicalTrials.gov |
What this trial studies
This study evaluates an artificial intelligence-based algorithm designed to support clinical decision-making for patients undergoing invasive mechanical ventilation. The algorithm aims to optimize ventilator settings based on individual patient characteristics and clinical guidelines, addressing the risks associated with inappropriate ventilation. By learning from deviations in expert handling and patient conditions, the AI system seeks to enhance patient outcomes in the intensive care unit. The study is observational and focuses on patients who have been on mechanical ventilation for more than four hours.
Who should consider this trial
Good fit: Ideal candidates for this study are adults aged 18 years or older who require invasive mechanical ventilation for more than four hours.
Not a fit: Patients receiving one-lung ventilation may not benefit from this study due to the specific focus on invasive mechanical ventilation settings.
Why it matters
Potential benefit: If successful, this approach could lead to improved patient outcomes by minimizing ventilator-induced lung injury and optimizing mechanical ventilation strategies.
How similar studies have performed: While the use of artificial intelligence in clinical decision support is a growing field, this specific application in optimizing mechanical ventilation settings is relatively novel and has not been extensively tested in prior studies.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: • Subjects who are 18 years or older and receive invasive mechanical ventilation for \> 4 hours Exclusion Criteria: • Patients receiving one-lung ventilation
Where this trial is running
Cleveland, Ohio and 7 other locations
- Cleveland Clinic Foundation, Cleveland, USA — Cleveland, Ohio, United States (RECRUITING)
- University Hospital Carl Gustav Carus Dresden — Dresden, Germany (RECRUITING)
- Institut Fur Angewandte Informatik (Infai) Ev — Leipzig, Germany (ACTIVE_NOT_RECRUITING)
- Institut Mihajlo Pupin — Belgrade, Serbia (ACTIVE_NOT_RECRUITING)
- Better Care Sl — Sabadell, Spain (ACTIVE_NOT_RECRUITING)
- Fundacio Parc Tauli — Sabadell, Spain (COMPLETED)
- Fundacion Publica Andaluza Progreso Y Salud — Seville, Spain (ACTIVE_NOT_RECRUITING)
- Inselspital, Universitätsspital Bern — Bern, Switzerland (COMPLETED)
Study contacts
- Principal investigator: Jakob Wittenstein, MD — University Hospital Carl Gustav Carus at Technischen Universität Dresden, Germany
- Study coordinator: Jakob Wittenstein, MD
- Email: jakob.wittenstein@ukdd.de
- Phone: +49 351 458 19887
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions: Invasive Mechanical Ventilation, Mechanical ventilation, ventilator-induced lung injury, ARDS, artificial intelligence