AI Assisted Preoperative Assessment for ASA Classification and ICU Admission

AI Assisted Clinical Decision-making in Preoperative Anesthesia Assessment: a Comparision of Clinicians, ChatGPT and Gemini

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT07783334

Enrollment

2500

Registered

2026-08-24

Start date

2026-02-16

Completion date

2026-08-20

Last updated

2026-08-24

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Preoperative Anesthesia Assesment

Keywords

artificial intteligence, preoperative assessment, ASA physical status classification, Intensive Care Unit admission, ChatGPT, Gemini, Anesthesiology

Brief summary

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.

Interventions

OTHERAI-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.

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Healthy volunteers

Yes

Inclusion criteria

* Age 18 years or older * Scheduled for elective surgery * Evaluated in the preoperative anesthesia clinic * Provision of informed consent

Exclusion criteria

* Pregnancy * Presence of an upper respiratory tract infection * Active herpes infection or active wound and/or lesion in the anesthesia-related area * Age under 18 years * Emergency surgery * Planned cardiovascular surgery * Incomplete clinical data

Design outcomes

Primary

Measure	Time frame	Description
Agreement in ASA Physical Status Classification	During preoperative assessment	Agreement between clinician-assigned and AI-generated ASA Physical Status classifications will be evaluated for ChatGPT and Gemini using linear weighted kappa statistics.

Secondary

Measure	Time frame	Description
Prediction of Postoperative ICU Admission	Within the first 24 hours after surgery	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.

Countries

Turkey (Türkiye)

Contacts

STUDY_DIRECTORevrim kucur tülübaş, MD

Bakirkoy Dr. Sadi Konuk Research and Training Hospital

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Aug 25, 2026