The Success of ChatGPT in Providing American Society of Anesthesiologist (ASA) Scores

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.

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.

Eligibility Criteria:
Inclusion Criteria:

* Patient who admitted to anesthesia clinics for both hospital
* Patient with ASA scores between I-IV

Exclusion Criteria:

* 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