AI-Based ASA Classification in Preoperative Patients

NCT07407998 | Completed

• 1 other identifier: Bursa City Hospital 004
• Study Type: observational
• Target: 200
• Locations: 1 country
• Sites: 1

Brief Summary

This prospective observational study aims to evaluate the performance of multiple artificial intelligence-based large language models in assigning American Society of Anesthesiologists Physical Status (ASA-PS) classifications in adult preoperative patients. AI-generated ASA scores obtained using both prompted and unprompted clinical scenario inputs will be compared with assessments performed by experienced anesthesiologists. The agreement, accuracy, readability, and overall quality of AI outputs will be analyzed to determine the potential role of artificial intelligence in supporting preoperative risk stratification.

Conditions

Preoperative Risk Assessment; ASA Physical Status Classification

Keywords

Artificial Intelligence; Large Language Models; Preoperative Evaluation; ASA Classification

Outcome Measures

Primary Outcomes (1)

• Agreement Between AI-Generated and Clinician-Assigned ASA Physical Status Classification

  Level of agreement between artificial intelligence models and anesthesiologists in assigning ASA Physical Status classification measured using Cohen's Kappa coefficient

  Preprocedural/Perioperative

Secondary Outcomes (2)

• Accuracy of AI Models in ASA Classification

  Preprocedural/Perioperative

• Readability of AI-Generated Clinical Responses

  Preprocedural/Perioperative

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

The study population consists of adult patients presenting for routine preoperative anesthesia assessment at Bursa City Hospital, including individuals with varying comorbidities and surgical risk profiles.

You may qualify if:

• Adult patients aged 18 years or older
• Undergoing routine preoperative anesthesia evaluation
• Classified as ASA Physical Status I-IV
• Availability of complete clinical data required for AI assessment

You may not qualify if:

• Patients younger than 18 years
• Refusal to participate
• Incomplete or missing clinical information

Sponsors & Collaborators

• Bursa City Hospital: lead

Study Sites (1)

Bursa City Hospital

Bursa, Nilüfer, 16110, Turkey (Türkiye)

Location

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER GOV
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: assos proc.

Study Record Dates

• First Submitted: February 4, 2026
• First Posted: February 12, 2026
• Study Start: December 15, 2024
• Primary Completion: December 15, 2024
• Study Completion: January 15, 2026
• Last Updated: February 12, 2026

Record last verified: 2026-02

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)