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Evaluation of the Success of Artificial Intelligence Models in Interpreting Arterial Waveform Analysis Data

StatusRecruiting
PhaseNot specified
Started
View on ClinicalTrials.gov ↗
Record status
This record was last updated March 4, 2025 (before its estimated August 15, 2025 completion). Its status may not reflect the trial's current state.

Record History

  1. Trial status: Not Yet Recruiting to Recruiting
    • Site details revised
    v3
  2. Secondary endpoints: details revised at 2 of 2 entriesv2
  3. Study First Submitted
  • Stopped: an ongoing trial was terminated, suspended or withdrawn.
  • Notable: the trial’s plan changed such as a big move in its timeline or size, a new primary endpoint, sponsor or phase, or recruiting opened or resumed.
  • Minor: routine progress and housekeeping, such as sites added or enrollment closed.
The goal of this observational study is to evaluate the ability of artificial intelligence (AI) models to interpret arterial waveform analysis data obtained from a hemodynamic monitoring system in adult patients undergoing elective surgery. The main questions it aims to answer are: Can AI models (ChatGPT-4 and Gemini 2.0) accurately detect hemodynamic abnormalities in arterial waveform data? How well do AI-generated diagnoses align with expert anesthesiologist assessments? Are AI-generated treatment recommendations clinically appropriate? Participants will: Undergo standard hemodynamic monitoring with an arterial waveform analysis device (MostCare). Have their anonymized hemodynamic data analyzed by AI models for abnormality detection, diagnosis suggestions, and treatment recommendations. Have AI-generated results reviewed and validated by experienced anesthesiologists. This study aims to assess whether AI models can serve as decision-support tools in perioperative and critical care settings by improving the interpretation of complex hemodynamic data, potentially enhancing patient safety, diagnostic accuracy, and clinical efficiency.
Trial Details
NCT Number NCT06828575
Lead Sponsor Kanuni Sultan Suleyman Training and Research Hospital
Conditions
(from sponsor)		 Hemodynamic Instability
Enrollment 145 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov