Artificial IntelligenceNCT06321328
Success of ChatGPT in Determining the Need for Postoperative Intensive Care
An observational study of Artificial Intelligence and Intensive Care Unit, run by Kanuni Sultan Suleyman Training and Research Hospital at 1 site in Turkey (Türkiye).
Trial summary
This is a prospective, observational study to be conducted at Sağlık Bilimleri University Istanbul Kanuni Sultan Süleyman Training and Research Hospital and Başakşehir Çam and Sakura City Hospital. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Artificial Intelligence, Intensive Care Unit, PACU Length of Stay
- How many people
- 406 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 16 Mar 2024to 1 Aug 2024
- How long will I take part?
- 30 Days
- 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: All patients over 18 years of age with ASA score III or IV or who underwent surgery in two hospitals where intensive care follow-up was recommended in the postoperative period will be included in the study.
Who may be able to join
- Patients 18 years of age and older Patients with ASA scores III and IV who were scheduled for surgery.
Who cannot join
- Lack of consent of the patient or relatives, Patients undergoing cardiovascular surgery and pediatric cardiovascular surgery.
- Patients with ASA score I-II-V-VI. Patients under 18 years of age Emergency cases Operations with surgical complications Operations with anesthetic complications
Trial locations and contacts
1 site in 1 country.
Turkey (Türkiye)1 site
istanbul Kanuni Sultan Süleyman Education and Training Hospital
Istanbul, 34303
About this study
Official title: Evaluation of the Success of ChatGPT-4 in Predicting Postoperative Intensive Care Needs and Mortality: Prospective Observational Study
This is a prospective, observational study to be conducted at Sağlık Bilimleri University Istanbul Kanuni Sultan Süleyman Training and Research Hospital and Başakşehir Çam and Sakura City Hospital. The study aims to record various preoperative and postoperative data of patients who have undergone surgeries, specifically those with ASA scores of III and IV or those indicated to potentially need postoperative intensive care. Data points include patient demographics, type of surgery, ASA score, comorbidities, lab and imaging findings, and both actual and ChatGPT version 4 predicted outcomes regarding postoperative intensive care needs, anesthesia methods, duration of stay in intensive care and the hospital, and 30-day mortality rates. ChatGPT version 4's predictions will be compared with actual outcomes and anesthesiologist decisions.
Read the detailed description
A Prospective, Observational Study to be Conducted at Sağlık Bilimleri University Istanbul Kanuni Sultan Süleyman Training and Research Hospital, Başakşehir Çam and Sakura City Hospital. In the study, age, surgery, additional diseases, abnormal laboratory findings, and imaging results of patients who have undergone preoperative anesthesia examination and received an ASA score of III and IV, or have been indicated to potentially need postoperative intensive care during the anesthesia examination will be recorded. Patients' surgeries are stated to be without complications, and predictions will be requested from the ChatGPT version 4 regarding the need for postoperative intensive care monitoring, recommended anesthesia method, strategies to reduce mortality, duration of stay in intensive care, and duration of hospital stay. These predictions will be compared with the decisions given by the anesthesiologist.
We will record these data:
Age: Patient's age. Gender: Patient's gender. Type of Surgery: The specific surgery the patient underwent. ASA Score: The American Society of Anesthesiologists (ASA) score indicating the patient's preoperative physical status.
Additional Diseases: Any comorbid conditions the patient has. Significant Laboratory Findings: Key lab results that could influence patient care.
Imaging Findings: Results from imaging studies relevant to the patient's condition or surgery.
ChatGPT-4's Intensive Care Prediction: Prediction made by ChatGPT version 4 regarding the need for postoperative intensive care.
Actual Need for Intensive Care: Whether the patient actually required postoperative intensive care.
Recommended Type of Anesthesia (ChatGPT-4): Anesthesia method suggested by ChatGPT version 4.
Type of Anesthesia Administered: The anesthesia method actually used during surgery.
Duration of Stay in Intensive Care: The actual length of time the patient spent in intensive care.
Intensive Care Stay Prediction (ChatGPT): ChatGPT version 4's prediction of how long the patient would need to stay in intensive care.
Total Hospital Stay Duration: The actual total length of the patient's hospital stay.
Total Hospital Stay Duration (ChatGPT): Prediction by ChatGPT version 4 of the total duration of the patient's hospital stay.
Mortality (Within 30 Days): Whether the patient died within 30 days of surgery. Mortality Prediction (ChatGPT): ChatGPT version 4's prediction regarding the patient's risk of mortality within 30 days post-surgery.
At Kanuni Sultan Süleyman Training and Research Hospital, the patient will be under the care of Specialist Doctor Engin İhsan Turan, and at Başakşehir Çam and Sakura City Hospital, under the care of Specialist Doctor Abdurrahman Engin Baydemir.
Primary Objective: To evaluate the success of ChatGPT-4 in predicting postoperative intensive care needs and mortality in adult patients with ASA scores of III and IV.
Secondary Objectives: To examine the effectiveness of ChatGPT-4's anesthesia method recommendations and additional suggestions in the clinical decision-making process.
Benefits: Understanding the contributions of artificial intelligence-based systems to clinical decision-making processes.
Risks: The potential for ChatGPT-4's recommendations to be misleading, however, the fact that doctors are the final decision-makers will mitigate this risk.
For the purpose of conducting statistical analysis, the data provided by ChatGPT will be compared with the actual data using IBM SPSS 21 software. For the categorical variable of the need for intensive care, the McNemar Exact test will be conducted.
- Keywords
- artificial intelligence
What is being measured
The primary outcome is the main question the study is designed to answer.
Intensive care predictions
intensive care predictions provided from ChatGpt will be compared with the decisions given by anesthesiologists
Measured: 3 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted20 Mar 2024
- Study start16 Mar 2024
- Primary completion16 Jul 2024
- Study completion1 Aug 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Artificial IntelligenceStudies 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
- Case only
- Time perspective
- Prospective
- Enrolment
- 406 participants (actual)
- Target duration
- 30 Days
Sponsor and investigators
- Lead sponsor
- Kanuni Sultan Suleyman Training and Research Hospital
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Engin Ihsan Turan, Kanuni Sultan Suleyman Training and Research Hospital
- Investigators
- Engin ihsan Turan, Principal investigator, Health Science University İstanbul Kanuni Sultan Süleyman Education and Training Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06321328
- Sponsor's protocol ID
- ChatGpt postoperative ICU
- Status last verified
- Mar 2024
- First submitted
- 14 Mar 2024
- Last updated
- 19 Sep 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Yeo YH, Samaan JS, Ng WH, Ting PS, Trivedi H, Vipani A, Ayoub W, Yang JD, Liran O, Spiegel B, Kuo A. Assessing the performance of ChatGPT in answering questions regarding cirrhosis and hepatocellular carcinoma. Clin Mol Hepatol. 2023 Jul;29(3):721-732. doi: 10.3350/cmh.2023.0089. Epub 2023 Mar 22.
PubMed 36946005
Study at a glance
From the registry record, last updated by the sponsor on 19 Sep 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of the Success of ChatGPT-4 in Predicting Postoperative Intensive Care Needs and Mortality: Prospective Observational Study
- ClinicalTrials.gov ID
- NCT06321328
- Acronym / sponsor ID
- ChatGpt postoperative ICU
- Keywords
- artificial intelligence
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 406 participants (actual)
- Lead sponsor
- Kanuni Sultan Suleyman Training and Research HospitalUniversity, hospital or other
- Study start
- 16 Mar 2024 (actual)
- Primary completion
- 16 Jul 2024 (actual)
- Study completion
- 1 Aug 2024 (actual)
- First posted
- 20 Mar 2024 (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.
This is a prospective, observational study to be conducted at Sağlık Bilimleri University Istanbul Kanuni Sultan Süleyman Training and Research Hospital and Başakşehir Çam and Sakura City Hospital. The study aims to record various preoperative and postoperative data of patients who have undergone surgeries, specifically those with ASA scores of III and IV or those indicated to potentially need postoperative intensive care. Data points include patient demographics, type of surgery, ASA score, comorbidities, lab and imaging findings, and both actual and ChatGPT version 4 predicted outcomes regarding postoperative intensive care needs, anesthesia methods, duration of stay in intensive care and the hospital, and 30-day mortality rates. ChatGPT version 4's predictions will be compared with actual outcomes and anesthesiologist decisions.
Detailed description
A Prospective, Observational Study to be Conducted at Sağlık Bilimleri University Istanbul Kanuni Sultan Süleyman Training and Research Hospital, Başakşehir Çam and Sakura City Hospital. In the study, age, surgery, additional diseases, abnormal laboratory findings, and imaging results of patients who have undergone preoperative anesthesia examination and received an ASA score of III and IV, or have been indicated to potentially need postoperative intensive care during the anesthesia examination will be recorded. Patients' surgeries are stated to be without complications, and predictions will be requested from the ChatGPT version 4 regarding the need for postoperative intensive care monitoring, recommended anesthesia method, strategies to reduce mortality, duration of stay in intensive care, and duration of hospital stay. These predictions will be compared with the decisions given by the anesthesiologist.
We will record these data:
Age: Patient's age. Gender: Patient's gender. Type of Surgery: The specific surgery the patient underwent. ASA Score: The American Society of Anesthesiologists (ASA) score indicating the patient's preoperative physical status.
Additional Diseases: Any comorbid conditions the patient has. Significant Laboratory Findings: Key lab results that could influence patient care.
Imaging Findings: Results from imaging studies relevant to the patient's condition or surgery.
ChatGPT-4's Intensive Care Prediction: Prediction made by ChatGPT version 4 regarding the need for postoperative intensive care.
Actual Need for Intensive Care: Whether the patient actually required postoperative intensive care.
Recommended Type of Anesthesia (ChatGPT-4): Anesthesia method suggested by ChatGPT version 4.
Type of Anesthesia Administered: The anesthesia method actually used during surgery.
Duration of Stay in Intensive Care: The actual length of time the patient spent in intensive care.
Intensive Care Stay Prediction (ChatGPT): ChatGPT version 4's prediction of how long the patient would need to stay in intensive care.
Total Hospital Stay Duration: The actual total length of the patient's hospital stay.
Total Hospital Stay Duration (ChatGPT): Prediction by ChatGPT version 4 of the total duration of the patient's hospital stay.
Mortality (Within 30 Days): Whether the patient died within 30 days of surgery. Mortality Prediction (ChatGPT): ChatGPT version 4's prediction regarding the patient's risk of mortality within 30 days post-surgery.
At Kanuni Sultan Süleyman Training and Research Hospital, the patient will be under the care of Specialist Doctor Engin İhsan Turan, and at Başakşehir Çam and Sakura City Hospital, under the care of Specialist Doctor Abdurrahman Engin Baydemir.
Primary Objective: To evaluate the success of ChatGPT-4 in predicting postoperative intensive care needs and mortality in adult patients with ASA scores of III and IV.
Secondary Objectives: To examine the effectiveness of ChatGPT-4's anesthesia method recommendations and additional suggestions in the clinical decision-making process.
Benefits: Understanding the contributions of artificial intelligence-based systems to clinical decision-making processes.
Risks: The potential for ChatGPT-4's recommendations to be misleading, however, the fact that doctors are the final decision-makers will mitigate this risk.
For the purpose of conducting statistical analysis, the data provided by ChatGPT will be compared with the actual data using IBM SPSS 21 software. For the categorical variable of the need for intensive care, the McNemar Exact test will be conducted.
Study design
- Observational model
- Case only
- Time perspective
- Prospective
- Target follow-up
- 30 Days
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- All patients over 18 years of age with ASA score III or IV or who underwent surgery in two hospitals where intensive care follow-up was recommended in the postoperative period will be included in the study.
Key inclusion criteria (1 listed)
- Patients 18 years of age and older Patients with ASA scores III and IV who were scheduled for surgery.
Key exclusion criteria (2 listed)
- Lack of consent of the patient or relatives, Patients undergoing cardiovascular surgery and pediatric cardiovascular surgery.
- Patients with ASA score I-II-V-VI. Patients under 18 years of age Emergency cases Operations with surgical complications Operations with anesthetic complications
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Intensive care predictions
Time frame: 3 months
intensive care predictions provided from ChatGpt will be compared with the decisions given by anesthesiologists
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 19 Sep 2024.
- Background: PubMed 36946005Yeo YH, Samaan JS, Ng WH, Ting PS, Trivedi H, Vipani A, Ayoub W, Yang JD, Liran O, Spiegel B, Kuo A. Assessing the performance of ChatGPT in answering questions regarding cirrhosis and hepatocellular carcinoma. Clin Mol Hepatol. 2023 Jul;29(3):721-732. doi: 10.3350/cmh.2023.0089. Epub 2023 Mar 22.
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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.
Engin ihsan Turan principal investigator
Health Science University İstanbul Kanuni Sultan Süleyman Education and Training 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 Artificial Intelligence and Intensive Care Unit, run by Kanuni Sultan Suleyman Training and Research Hospital 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 1 inclusion and 2 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 19 Sep 2024. 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?
Intensive care predictions (time frame: 3 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06321328, which also lists 1 linked publication.
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 19 Sep 2024.