Evaluating AI Models for ICU Patient Discharge Decisions
The Evaluation of the Effectiveness of General Artificial Intelligence Models in Extubation Decision-Making in the Intensive Care Unit
This study is testing if AI tools like ChatGPT and Gemini can help doctors decide the best time to discharge patients from the ICU to improve their recovery and make better use of hospital resources.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 398 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Kanuni Sultan Suleyman Training and Research Hospital Academic / other |
| Locations | 1 site (Istanbul, Küçükçekmece) |
| Trial ID | NCT06584890 on ClinicalTrials.gov |
What this trial studies
This study evaluates the effectiveness of General Artificial Intelligence models, specifically ChatGPT and Gemini, in assisting clinicians with discharge decisions for patients in the Intensive Care Unit (ICU). It aims to determine if these AI models can accurately predict the optimal timing for patient discharge, thereby improving patient outcomes and resource utilization. The study will collect comprehensive clinical data from ICU patients and use machine learning techniques to analyze this data, comparing AI predictions with the decisions made by ICU specialists. Statistical methods will be employed to assess the accuracy and reliability of the AI models in predicting discharge suitability.
Who should consider this trial
Good fit: Ideal candidates for this study are patients aged 18 years or older who are currently admitted to the ICU and have sufficient clinical data available for analysis.
Not a fit: Patients receiving palliative care or those whose discharge is not anticipated will not benefit from this study.
Why it matters
Potential benefit: If successful, this study could enhance the accuracy and efficiency of discharge decisions, leading to improved patient outcomes and better resource management in ICUs.
How similar studies have performed: While the use of AI in clinical decision-making is an emerging field, similar studies have shown promise in improving decision accuracy, though this specific application remains novel.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Patients aged 18 years or older. * Patients currently admitted to the Intensive Care Unit (ICU) during the study -period. * Patients with sufficient clinical data available in the hospital\'s information system, including demographic information, clinical indicators, and treatment history. * Patients for whom a discharge decision (to a general ward or home) needs to be made during their ICU stay. Exclusion Criteria: * Patients younger than 18 years old. Patients with incomplete or insufficient clinical data in the hospital\'s information system, making it difficult to assess their condition accurately. Patients who are in the ICU for palliative care or end-of-life care, where discharge to a general ward or home is not anticipated. Patients who have opted out of participating in the study or whose legal representatives have declined participation.
Where this trial is running
Istanbul, Küçükçekmece
- Health Science University İstanbul Prof Dr Cemil Taşcıoğlu City Hospital — Istanbul, Küçükçekmece, Turkey (Recruiting)
Study contacts
- Principal investigator: Engin ihsan turan — Health Science University İstanbul Kanuni Sultan Süleyman Education and Training Hospital
- Study coordinator: engin ihsan turan, dr
- Email: enginihsan@hotmail.com
- Phone: +905382431114
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.