Success of ChatGPT in Determining the Need for Postoperative Intensive Care

September 17, 2024 updated by: Engin Ihsan Turan, Kanuni Sultan Suleyman Training and Research Hospital

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.

Study Overview

Status

Completed

Conditions

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 Type

Observational

Enrollment (Actual)

406

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Turkey
      • Istanbul, Turkey, 34303
        • istanbul Kanuni Sultan Süleyman Education and Training Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Probability Sample

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.

Description

Inclusion Criteria:

  • Patients 18 years of age and older Patients with ASA scores III and IV who were scheduled for surgery.

Exclusion Criteria:

  • 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

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Intensive care predictions
Time Frame: 3 months
intensive care predictions provided from ChatGpt will be compared with the decisions given by anesthesiologists
3 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Kanuni Sultan Suleyman Training and Research Hospital

Investigators

  • Principal Investigator: Engin ihsan turan, Health Science University İstanbul Kanuni Sultan Süleyman Education and Training Hospital

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

March 16, 2024

Primary Completion (Actual)

July 16, 2024

Study Completion (Actual)

August 1, 2024

Study Registration Dates

First Submitted

March 14, 2024

First Submitted That Met QC Criteria

March 14, 2024

First Posted (Actual)

March 20, 2024

Study Record Updates

Last Update Posted (Actual)

September 19, 2024

Last Update Submitted That Met QC Criteria

September 17, 2024

Last Verified

March 1, 2024

More Information

Terms related to this study

Keywords

Other Study ID Numbers

  • ChatGpt postoperative ICU

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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