An observational study in Preoperative Anesthesia Assesment, sponsored by Bakirkoy Dr. Sadi Konuk Research and Training Hospital. Active, not recruiting at 1 site in Turkey (Türkiye). Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-08-24.
Sponsored by Bakirkoy Dr. Sadi Konuk Research and Training Hospital · Observational
This prospective observational study evaluates the performance of artificial intelligence (AI) models in preoperative anesthesia assessment. Preoperative clinical data from adult patients undergoing elective surgery are independently evaluated by clinicians and AI models (ChatGPT and Gemini). The study compares their assessments of American Society of Anesthesiologists (ASA) physical status classification and the predicted need for intensive care unit (ICU) admission within the first 24 hours after surgery. Actual postoperative ICU admission is used as the clinical outcome for evaluating predictive performance. No treatment or clinical decision is determined by the AI models, and patient management is performed according to routine clinical practice.
Adult patients undergoing elective surgery who are evaluated in the preoperative anesthesia clinic at Bakirkoy Dr. Sadi Konuk Research and Training Hospital.
Exclusion Criteria:
Adult patients undergoing elective surgery who undergo routine preoperative anesthesia assessment. Preoperative clinical data from each participant are independently evaluated by the clinician and the AI models ChatGPT and Gemini for ASA physical status classification and prediction of ICU admission within the first 24 postoperative hours. AI assessments do not influence clinical management or patient care.
Other: AI-assisted preoperative assesment
Preoperative clinical data are independently evaluated using ChatGPT and Gemini for ASA physical status classification and prediction of ICU admission within 24 hours after surgery. AI-generated assessments are used for research purposes only and do not influence clinical decision-making or patient care.
Agreement in ASA Physical Status Classification
Agreement between clinician-assigned and AI-generated ASA Physical Status classifications will be evaluated for ChatGPT and Gemini using linear weighted kappa statistics.
Time frame: During preoperative assessment
Prediction of Postoperative ICU Admission
The accuracy of preoperative predictions of postoperative ICU admission made by the clinician, ChatGPT, and Gemini will be evaluated against actual ICU admission occurring within the first 24 hours after surgery. Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy will be calculated for each evaluator.
Time frame: Within the first 24 hours after surgery
Plan to share: No — Individual participant data will not be shared due to patient confidentiality and data protection considerations.
No publications or documents are linked to this record.
This study is active, not recruiting, as verified in Aug 2026. You cannot join it, but the record below documents what was studied.
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Bakirkoy Dr. Sadi Konuk Research and Training Hospital