Artificial IntelligenceASANCT06321445
The Success of ChatGPT in Providing American Society of Anesthesiologist (ASA) Scores
An observational study of Artificial Intelligence and Preoperative Evaluation, run by Kanuni Sultan Suleyman Training and Research Hospital at 1 site in Turkey (Türkiye).
Trial summary
Patients applied to the anesthesia clinics of Health Science University Istanbul Kanuni Sultan Suleyman Training and Research Hospital and Basaksehir Cam and Sakura City Hospital were included in the study. Evaluation forms which will be filled in every preoperative examinations will be saved in the hospitals systems. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Artificial Intelligence, Preoperative Evaluation
- What is being tested?
- providing ASA score
- How many people
- 2,851 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 8 Feb 2024to 1 May 2024
- How long will I take part?
- 1 Day
- 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 Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: All patients who admitted to anesthesia clinics of Health Science University Istanbul Kanuni Sultan Suleyman Training and Research Hospital and Basaksehir Cam and Sakura City Hospital.
Who may be able to join
- Patient who admitted to anesthesia clinics for both hospital
- Patient with ASA scores between I-IV
Who cannot join
- ASA scores higher than IV
- Emergency cases patients have symptoms like upper and lower airway infections.
- patients haven't got enough informations to provide ASA scores.
- Patients with symptoms of an active upper or lower respiratory tract infection
Trial locations and contacts
1 site in 1 country.
Turkey (Türkiye)1 site
Health Science University İstanbul Kanuni Sultan Süleyman Education and Training Hospital
Istanbul, 34303
About this study
Patients applied to the anesthesia clinics of Health Science University Istanbul Kanuni Sultan Suleyman Training and Research Hospital and Basaksehir Cam and Sakura City Hospital were included in the study. Evaluation forms which will be filled in every preoperative examinations will be saved in the hospitals systems. Patients datas without indentification informations will be asked to ChatGpt to give anesthesiological risc scores. This scores will be compared with the scores already given by anesthesiologists.
Read the detailed description
Patients of all ages and sexes with ASA scores ranging from I to IV who applied to the anesthesia clinics of Health Science University Istanbul Kanuni Sultan Suleyman Training and Research Hospital and Basaksehir Cam and Sakura City Hospital were included in the study. Patients with ASA scores of V and VI were not included in the study as their statistical distribution would be disrupted.
Data Collection Data were collected daily from preoperative examination evaluation forms in this study, which included Patient's Age Patient's Gender Patient's Weight Patient's Height Additional Illnesses Medications Used Abnormal Laboratory Findings Abnormal Imaging Findings Operation to be Performed Consultation Notes Given ASA Score ChatGPT's ASA Score. At Health Science University Istanbul Kanuni Sultan Suleyman Training and Research Hospita, the patient will be under the care of Specialist Doctor Engin İhsan Turan, and at Basaksehir Cam and Sakura City Hospital, under the care of Specialist Doctor Abdurrahman Engin Baydemir.
The natural language processing module ChatGPT 4, developed by OpenAI, was consulted for providing ASA scores based on the collected data. In addition to the collected data, ASA scores given by anesthesia experts were also entered into the system.
The investigators chose ChatGPT-4 among artificial intelligence models for our study due to its extensive use in the literature.
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 recommendations on anesthesia methods 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, but the risk will be mitigated by doctors being the final decision-makers.
Use of ChatGPT 4 After the data mentioned above regarding the patients were transmitted to ChatGPT 4, ChatGPT 4 was asked to predict the ASA scores of the patients. To do so the investigators will create a special GPT which can provide ASA scores according to the newest guidelines. This GPT will assign patients an ASA score based on abnormal data while recognizing that the patients' other results and physical examination findings are normal.
- Conditions
- Artificial Intelligence, Preoperative Evaluation
- Being tested
- providing ASA score
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
providing ASA scoreOther
ASA scoring, or the American Society of Anesthesiologists (ASA) Physical Status Classification System, is a framework used by anesthesiologists to assess the preoperative physical fitness of a patient before surgery. It categorizes patients into six classes based on their overall health status, ranging from ASA I (a healthy patient) to ASA VI (a declared brain-dead patient whose organs are being removed for donor purposes). The ASA score helps in predicting perioperative risks and assists healthcare professionals in making informed decisions about anesthesia management and the need for special precautions during and after surgery.
| Study group | Role | What they receive |
|---|---|---|
| Experts | ASA scores provided by anesthesiologists Receives: Other: providing ASA score | |
| ChatGpt | ASA scores provided by ChatGpt Receives: Other: providing ASA score |
What is being measured
The primary outcome is the main question the study is designed to answer.
The Success of ChatGPT in Providing American Society of Anesthesiologist (ASA) Scores
Comparison of ASA scores provided from ChatGpt and provided from anesthesiologists.
ASA 1: A normal healthy patient. ASA 2: A patient with mild systemic disease. ASA 3: A patient with severe systemic disease that is not incapacitating. ASA 4: A patient with severe systemic disease that is a constant threat to life.
ASA 5: A moribund patient who is not expected to survive without the operation. ASA 6: A declared brain-dead patient whose organs are being removed for donor purposes.
Additional classifications include:
E: This designation can be added to any of the above classifications (ASA 1E to ASA 6E) to indicate that the surgery is an emergency, which increases the risk of the procedure.
Measured: 2 weeks
Secondary outcomes (1)
The Success of ChatGPT in clinical decisions
Comparison of ASA scores provided from ChatGpt and provided from anesthesiologists.
ASA 1: A normal healthy patient. ASA 2: A patient with mild systemic disease. ASA 3: A patient with severe systemic disease that is not incapacitating. ASA 4: A patient with severe systemic disease that is a constant threat to life.
ASA 5: A moribund patient who is not expected to survive without the operation. ASA 6: A declared brain-dead patient whose organs are being removed for donor purposes.
Additional classifications include:
E: This designation can be added to any of the above classifications (ASA 1E to ASA 6E) to indicate that the surgery is an emergency, which increases the risk of the procedure.
Measured: 2 weeks
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 start8 Feb 2024
- Primary completion1 Apr 2024
- Study completion1 May 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)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
- 2,851 participants (actual)
- Target duration
- 1 Day
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, Specialist, Principal investigator, Health Science University İstanbul Kanuni Sultan Süleyman Education and Training Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06321445
- Sponsor's protocol ID
- ChatGptASAscore
- Acronym
- ASA
- Status last verified
- May 2024
- First submitted
- 11 Mar 2024
- Last updated
- 6 May 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- 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 36946005Wongtangman K, Aasman B, Garg S, Witt AS, Harandi AA, Azimaraghi O, Mirhaji P, Soby S, Anand P, Himes CP, Smith RV, Santer P, Freda J, Eikermann M, Ramaswamy P. Development and validation of a machine learning ASA-score to identify candidates for comprehensive preoperative screening and risk stratification. J Clin Anesth. 2023 Aug;87:111103. doi: 10.1016/j.jclinane.2023.111103. Epub 2023 Mar 8.
PubMed 36898279Turan EI, Baydemir AE, Ozcan FG, Sahin AS. Evaluating the accuracy of ChatGPT-4 in predicting ASA scores: A prospective multicentric study ChatGPT-4 in ASA score prediction. J Clin Anesth. 2024 Sep;96:111475. doi: 10.1016/j.jclinane.2024.111475. Epub 2024 Apr 23.
PubMed 38657530
Study at a glance
From the registry record, last updated by the sponsor on 6 May 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Success of ChatGPT in Providing American Society of Anesthesiologist (ASA) Scores
- ClinicalTrials.gov ID
- NCT06321445
- Acronym / sponsor ID
- ASA / ChatGptASAscore
- Conditions
- Artificial Intelligence, Preoperative Evaluation
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 2,851 participants (actual)
- Lead sponsor
- Kanuni Sultan Suleyman Training and Research HospitalUniversity, hospital or other
- Study start
- 8 Feb 2024 (actual)
- Primary completion
- 1 Apr 2024 (actual)
- Study completion
- 1 May 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.
Patients applied to the anesthesia clinics of Health Science University Istanbul Kanuni Sultan Suleyman Training and Research Hospital and Basaksehir Cam and Sakura City Hospital were included in the study. Evaluation forms which will be filled in every preoperative examinations will be saved in the hospitals systems. Patients datas without indentification informations will be asked to ChatGpt to give anesthesiological risc scores. This scores will be compared with the scores already given by anesthesiologists.
Detailed description
Patients of all ages and sexes with ASA scores ranging from I to IV who applied to the anesthesia clinics of Health Science University Istanbul Kanuni Sultan Suleyman Training and Research Hospital and Basaksehir Cam and Sakura City Hospital were included in the study. Patients with ASA scores of V and VI were not included in the study as their statistical distribution would be disrupted.
Data Collection Data were collected daily from preoperative examination evaluation forms in this study, which included Patient's Age Patient's Gender Patient's Weight Patient's Height Additional Illnesses Medications Used Abnormal Laboratory Findings Abnormal Imaging Findings Operation to be Performed Consultation Notes Given ASA Score ChatGPT's ASA Score. At Health Science University Istanbul Kanuni Sultan Suleyman Training and Research Hospita, the patient will be under the care of Specialist Doctor Engin İhsan Turan, and at Basaksehir Cam and Sakura City Hospital, under the care of Specialist Doctor Abdurrahman Engin Baydemir.
The natural language processing module ChatGPT 4, developed by OpenAI, was consulted for providing ASA scores based on the collected data. In addition to the collected data, ASA scores given by anesthesia experts were also entered into the system.
The investigators chose ChatGPT-4 among artificial intelligence models for our study due to its extensive use in the literature.
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 recommendations on anesthesia methods 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, but the risk will be mitigated by doctors being the final decision-makers.
Use of ChatGPT 4 After the data mentioned above regarding the patients were transmitted to ChatGPT 4, ChatGPT 4 was asked to predict the ASA scores of the patients. To do so the investigators will create a special GPT which can provide ASA scores according to the newest guidelines. This GPT will assign patients an ASA score based on abnormal data while recognizing that the patients' other results and physical examination findings are normal.
Study design
- Observational model
- Case only
- Time perspective
- Prospective
- Target follow-up
- 1 Day
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Experts | – | Other: providing ASA scoreASA scores provided by anesthesiologists |
| ChatGpt | – | Other: providing ASA scoreASA scores provided by ChatGpt |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- All patients who admitted to anesthesia clinics of Health Science University Istanbul Kanuni Sultan Suleyman Training and Research Hospital and Basaksehir Cam and Sakura City Hospital.
Key inclusion criteria (2 listed)
- Patient who admitted to anesthesia clinics for both hospital
- Patient with ASA scores between I-IV
Key exclusion criteria (4 listed)
- ASA scores higher than IV
- Emergency cases patients have symptoms like upper and lower airway infections.
- patients haven't got enough informations to provide ASA scores.
- Patients with symptoms of an active upper or lower respiratory tract infection
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 |
|---|---|---|
| providing ASA scoreASA scoring, or the American Society of Anesthesiologists (ASA) Physical Status Classification System, is a framework used by anesthesiologists to assess the preoperative physical fitness of a patient before surgery. It categorizes patients into six classes based on their overall health status, ranging from ASA I (a healthy patient) to ASA VI (a declared brain-dead patient whose organs are being removed for donor purposes). The ASA score helps in predicting perioperative risks and assists healthcare professionals in making informed decisions about anesthesia management and the need for special precautions during and after surgery. | Other | ChatGpt, Experts |
Primary outcome
The Success of ChatGPT in Providing American Society of Anesthesiologist (ASA) Scores
Time frame: 2 weeks
Comparison of ASA scores provided from ChatGpt and provided from anesthesiologists. ASA 1: A normal healthy patient. ASA 2: A patient with mild systemic disease. ASA 3: A patient with severe systemic disease that is not incapacitating. ASA 4: A patient with severe systemic disease that is a constant threat to life. ASA 5: A moribund patient who is not expected to survive without the operation. ASA 6: A declared brain-dead patient whose organs are being removed for donor purposes. Additional classifications include: E: This designation can be added to any of the above classifications (ASA 1E to ASA 6E) to indicate that the surgery is an emergency, which increases the risk of the procedure.
1 secondary outcome
The Success of ChatGPT in clinical decisions
Time frame: 2 weeks
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 6 May 2024.
- Results publication: 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.
- Results publication: PubMed 36898279Wongtangman K, Aasman B, Garg S, Witt AS, Harandi AA, Azimaraghi O, Mirhaji P, Soby S, Anand P, Himes CP, Smith RV, Santer P, Freda J, Eikermann M, Ramaswamy P. Development and validation of a machine learning ASA-score to identify candidates for comprehensive preoperative screening and risk stratification. J Clin Anesth. 2023 Aug;87:111103. doi: 10.1016/j.jclinane.2023.111103. Epub 2023 Mar 8.
- Derived from this study: PubMed 38657530Turan EI, Baydemir AE, Ozcan FG, Sahin AS. Evaluating the accuracy of ChatGPT-4 in predicting ASA scores: A prospective multicentric study ChatGPT-4 in ASA score prediction. J Clin Anesth. 2024 Sep;96:111475. doi: 10.1016/j.jclinane.2024.111475. Epub 2024 Apr 23.
- Individual participant dataSharing planned: No
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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, Specialist 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 Preoperative Evaluation, 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 2 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 6 May 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?
The Success of ChatGPT in Providing American Society of Anesthesiologist (ASA) Scores (time frame: 2 weeks). 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 NCT06321445, which also lists 3 linked publications.
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 6 May 2024.