Postoperative CareNCT07395791
Evaluation of ChatGPT-5 and Anesthesiologist Predictions of Postoperative Intensive Care Unit Admission Using Preoperative Clinical Data
An observational study of Postoperative Care, run by Beste Mutlu Dağlıoğlu at 1 site in Turkey (Türkiye).
Trial summary
Accurate prediction of postoperative intensive care unit (ICU) requirement is essential for patient safety and efficient use of limited ICU resources. In routine clinical practice, decisions regarding postoperative ICU admission are primarily based on anesthesiologists' preoperative clinical judgment, which may vary… Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Postoperative Care
- How many people
- 938 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 7 Dec 2025to 1 Jun 2026
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The study population consists of adult patients aged 18 years and older who underwent elective surgical procedures and received preoperative anesthesiology evaluation at a tertiary care hospital. The study includes patients for whom postoperative intensive care unit (ICU) requirement was assessed based on preoperative clinical data. Patient outcomes were evaluated according to actual postoperative ICU admission status.
Who may be able to join
- Adult patients aged 18 years or older.
- Patients undergoing elective surgical procedures requiring preoperative anesthesiology evaluation.
- Availability of complete preoperative clinical data required for postoperative intensive care unit (ICU) need prediction.
- Patients evaluated preoperatively by an anesthesiology specialist.
Who cannot join
- Patients younger than 18 years of age.
- Emergency surgical procedures.
- Patients with incomplete or missing preoperative clinical data.
- Patients who decline the use of their clinical data for research purposes.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Evaluation of the Agreement Between ChatGPT-5 and Anesthesiologists' Predictions and Actual Outcomes in Predicting Postoperative Intensive Care Unit Requirement Based on Preoperative Data
Accurate prediction of postoperative intensive care unit (ICU) requirement is essential for patient safety and efficient use of limited ICU resources. In routine clinical practice, decisions regarding postoperative ICU admission are primarily based on anesthesiologists' preoperative clinical judgment, which may vary among clinicians.
This prospective, observational study aims to evaluate the agreement between predictions made by ChatGPT-5(Chat Generative Pre-trained Transformer) and anesthesiologists regarding postoperative ICU requirement using routinely collected preoperative patient data, and to compare these predictions with actual postoperative ICU admission outcomes.
The study does not involve any intervention, treatment modification, or additional procedures beyond standard clinical care. All patient data are anonymized, and clinical management is not influenced by the model's predictions
Read the detailed description
Postoperative intensive care unit (ICU) admission is a critical component of perioperative patient management, particularly in patients with increased surgical or anesthetic risk. Accurate preoperative identification of patients who will require postoperative ICU care may improve patient safety and optimize resource allocation.
This study is designed as a prospective, non-interventional observational cohort study conducted in adult patients undergoing elective surgical procedures. Routinely collected preoperative clinical data, including demographic characteristics, comorbidities, laboratory results, and anesthesiologists' assessments, are recorded for each participant.
For each patient, postoperative ICU requirement predictions generated by ChatGPT-5 using structured preoperative data are documented. These predictions are compared with anesthesiologists' preoperative ICU admission assessments and with actual postoperative ICU admission outcomes.
No additional diagnostic or therapeutic interventions are performed as part of the study. Patient care follows standard institutional practice at all times. All collected data are anonymized prior to analysis. Statistical analyses focus on agreement and predictive performance measures, including sensitivity, specificity, and concordance between prediction methods and actual outcomes.
- Conditions
- Postoperative Care
- Being tested
- No intervention (observational study)
- Keywords
- Artificial Intelligence, ChatGPT, Anesthesiology, Intensive Care Unit, Postoperative Care, Risk Prediction
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
No intervention (observational study)Other
This is a non-interventional observational study. No therapeutic or diagnostic intervention is performed as part of the study.
What is being measured
The primary outcome is the main question the study is designed to answer.
Agreement Between Predicted and Actual Postoperative ICU Requirement
Agreement between preoperative predictions of postoperative intensive care unit (ICU) requirement made by ChatGPT-5 and anesthesiologists, compared with actual postoperative ICU admission outcomes.
Measured: Within the first 24 hours after surgery
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Feb 2026
- Study start7 Dec 2025
- Primary completion31 Dec 2025
- Study completion1 Jun 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Postoperative CareStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 938 participants (actual)
Sponsor and investigators
- Lead sponsor
- Beste Mutlu Dağlıoğlu
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor-investigator, Beste Mutlu Dağlıoğlu, Antalya City Hospital
- Investigators
- Beste Mutlu Dağlıoğlu, Principal investigator, Antalya City Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07395791
- Sponsor's protocol ID
- AntalyaCity
- Status last verified
- Jan 2026
- First submitted
- 1 Feb 2026
- Last updated
- 24 Jun 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 24 Jun 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of the Agreement Between ChatGPT-5 and Anesthesiologists' Predictions and Actual Outcomes in Predicting Postoperative Intensive Care Unit Requirement Based on Preoperative Data
- ClinicalTrials.gov ID
- NCT07395791
- Acronym / sponsor ID
- AntalyaCity
- Conditions
- Postoperative Care
- Keywords
- Artificial Intelligence, ChatGPT, Anesthesiology, Intensive Care Unit, Postoperative Care, Risk Prediction
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 938 participants (actual)
- Lead sponsor
- Beste Mutlu DağlıoğluUniversity, hospital or other
- Study start
- 7 Dec 2025 (actual)
- Primary completion
- 31 Dec 2025 (actual)
- Study completion
- 1 Jun 2026 (actual)
- First posted
- 9 Feb 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Accurate prediction of postoperative intensive care unit (ICU) requirement is essential for patient safety and efficient use of limited ICU resources. In routine clinical practice, decisions regarding postoperative ICU admission are primarily based on anesthesiologists' preoperative clinical judgment, which may vary among clinicians.
This prospective, observational study aims to evaluate the agreement between predictions made by ChatGPT-5(Chat Generative Pre-trained Transformer) and anesthesiologists regarding postoperative ICU requirement using routinely collected preoperative patient data, and to compare these predictions with actual postoperative ICU admission outcomes.
The study does not involve any intervention, treatment modification, or additional procedures beyond standard clinical care. All patient data are anonymized, and clinical management is not influenced by the model's predictions
Detailed description
Postoperative intensive care unit (ICU) admission is a critical component of perioperative patient management, particularly in patients with increased surgical or anesthetic risk. Accurate preoperative identification of patients who will require postoperative ICU care may improve patient safety and optimize resource allocation.
This study is designed as a prospective, non-interventional observational cohort study conducted in adult patients undergoing elective surgical procedures. Routinely collected preoperative clinical data, including demographic characteristics, comorbidities, laboratory results, and anesthesiologists' assessments, are recorded for each participant.
For each patient, postoperative ICU requirement predictions generated by ChatGPT-5 using structured preoperative data are documented. These predictions are compared with anesthesiologists' preoperative ICU admission assessments and with actual postoperative ICU admission outcomes.
No additional diagnostic or therapeutic interventions are performed as part of the study. Patient care follows standard institutional practice at all times. All collected data are anonymized prior to analysis. Statistical analyses focus on agreement and predictive performance measures, including sensitivity, specificity, and concordance between prediction methods and actual outcomes.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The study population consists of adult patients aged 18 years and older who underwent elective surgical procedures and received preoperative anesthesiology evaluation at a tertiary care hospital. The study includes patients for whom postoperative intensive care unit (ICU) requirement was assessed based on preoperative clinical data. Patient outcomes were evaluated according to actual postoperative ICU admission status.
Key inclusion criteria (4 listed)
- Adult patients aged 18 years or older.
- Patients undergoing elective surgical procedures requiring preoperative anesthesiology evaluation.
- Availability of complete preoperative clinical data required for postoperative intensive care unit (ICU) need prediction.
- Patients evaluated preoperatively by an anesthesiology specialist.
Key exclusion criteria (4 listed)
- Patients younger than 18 years of age.
- Emergency surgical procedures.
- Patients with incomplete or missing preoperative clinical data.
- Patients who decline the use of their clinical data for research purposes.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| No intervention (observational study)This is a non-interventional observational study. No therapeutic or diagnostic intervention is performed as part of the study. | Other | – |
Primary outcome
Agreement Between Predicted and Actual Postoperative ICU Requirement
Time frame: Within the first 24 hours after surgery
Agreement between preoperative predictions of postoperative intensive care unit (ICU) requirement made by ChatGPT-5 and anesthesiologists, compared with actual postoperative ICU admission outcomes.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Jun 2026.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Beste Mutlu Dağlıoğlu principal investigator
Antalya City Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Postoperative Care, run by Beste Mutlu Dağlıoğlu at 1 site in Turkey (Türkiye).
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 24 Jun 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Turkey (Türkiye). Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Agreement Between Predicted and Actual Postoperative ICU Requirement (time frame: Within the first 24 hours after surgery). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Jun 2026.