Comparison of Artificial Intelligence and Anesthesiologist in Preoperative Risk Assessment

NCT07364942 | Completed

• 1 other identifier: PREOP-AI-2025
• Study Type: observational
• Target: 500
• Locations: 1 country
• Sites: 1

Brief Summary

Preoperative evaluation is essential for identifying patient-related risks before elective surgery and for planning safe anesthesia management. Traditionally, this evaluation is performed by anesthesiologists based on clinical history, physical examination, comorbidities, and laboratory findings. This observational study aims to compare the clinical performance of a machine learning-based artificial intelligence system with anesthesiologist assessment during preoperative patient evaluation. The artificial intelligence system independently analyzes patient data and generates risk assessments, which are then compared with evaluations performed by anesthesiologists. The primary objective of the study is to assess the level of agreement between the artificial intelligence system and anesthesiologists in preoperative risk assessment. Secondary objectives include evaluating the accuracy and consistency of the artificial intelligence system and exploring its potential role as a decision-support tool in preoperative clinical practice. The findings of this study may contribute to understanding the potential benefits and limitations of artificial intelligence-assisted decision making in preoperative evaluation

Conditions

Preoperative Risk Assessment

Keywords

Preoperative assessment,Artificial intelligence

Outcome Measures

Primary Outcomes (1)

• Rate of Agreement Between Artificial Intelligence-Based and Anesthesiologist Preoperative Risk Assessments

  This outcome measures the level of agreement between an artificial intelligence-based preoperative evaluation system and anesthesiologist assessment, including American Society of Anesthesiologists (ASA) physical status classification and overall perioperative risk stratification. Agreement will be evaluated using appropriate statistical measures.

  At the time of preoperative evaluation

Eligibility Criteria

• Age: 18 Years - 99 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

The study population consists of adult patients aged 18 years and older who were scheduled for elective surgical procedures and underwent routine preoperative evaluation at a tertiary care university hospital. Preoperative risk assessments performed by anesthesiologists were compared with artificial intelligence-based risk assessments using the same clinical data.

You may qualify if:

• \- Adult patients aged 18 years and older
• Patients scheduled for elective surgery under anesthesia
• Patients who underwent routine preoperative evaluation
• Availability of complete preoperative clinical data required for both anesthesiologist and artificial intelligence-based assessment

You may not qualify if:

• \- Patients younger than 18 years
• Emergency surgery cases
• Patients with incomplete or missing preoperative clinical data
• Patients who declined participation or whose data could not be evaluated

Sponsors & Collaborators

• Gülgün Elif Aksoy: lead

Study Sites (1)

Trabzon Faculty of Medicine, Kanuni Training and Research Hospital,

Trabzon, Trabzon, Turkey (Türkiye)

Location

Study Officials

• Gülgün E Aksoy, MD

  Trabzon Faculty of Medicine, Kanuni Training and Research Hospital, Turkey

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR INVESTIGATOR
• PI Title: Specialist Physician in Anesthesiology and Reanimation

Study Record Dates

• First Submitted: January 10, 2026
• First Posted: January 23, 2026
• Study Start: March 1, 2025
• Primary Completion: May 1, 2025
• Study Completion: October 30, 2025
• Last Updated: January 23, 2026

Record last verified: 2026-01

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)