About this trial
This prospective multicenter observational study aims to evaluate the agreement between artificial intelligence (AI)-based interpretation and expert interpretation of rotational thromboelastometry (ROTEM) findings in clinically relevant settings. ROTEM is widely used to guide hemostatic therapy in perioperative and critically ill patients, but its interpretation is complex and subject to interobserver variability.
The primary objective is to determine whether AI-based interpretation achieves agreement comparable to variability between expert clinicians. Secondary objectives include comparison of interpretation time, assessment of consistency of AI outputs, and evaluation of potential differences in clinical decision-making.
ROTEM datasets will be independently assessed by multiple expert anesthesiologists and by an AI-based model using standardized input. Agreement between methods and variability of interpretation will be analyzed.
The study aims to determine whether AI-assisted interpretation could serve as a reliable decision-support tool and reduce variability in ROTEM-guided clinical practice.
Eligibility criteria
Qualifiers
ROTEM analysis performed using a ROTEM Sigma device as part of routine clinical care
Availability of complete ROTEM output (graphical and numerical data)
ROTEM measurement obtained in a clinical context where assessment of coagulation status is indicated (e.g., perioperative setting, trauma, or critical illness)
Disqualifiers
ROTEM measurements performed using the HEPTEM channel
Incomplete or missing ROTEM data preventing standardized evaluation
ROTEM measurements obtained under non-standardized or technically unreliable conditions
Trial design
Treatments tested in this trial
- Large Language Model (LLM) artificial intelligence assesment