Perioperative medicine & outcomes

Comparative performance of GPT-4 models and expert anaesthesiologists in peri-operative antithrombotic management: A cross-sectional evaluation

Eur J AnaesthesiolPublished Cross-sectional study

Authors' conclusion

In simulated peri-operative antithrombotic management scenarios, a domain-specific, transformer-based language model generated faster and more complete responses than clinician-generated answers, while accuracy was comparable across groups.

Study context

Population
25 hypothetical peri-operative scenarios involving anticoagulant or antiplatelet therapy, Spain25 scenarios
Exposure
Domain-specific model vs Anaesthesiologists
Outcome
Completeness and accuracy of responses, rated by three blinded experts
Methodological detailsanalytical, fully simulated, nonclinical environment, multicentre (five university-affiliated anaesthesiology departments), blinded expert rating
  • Analytical
  • Fully simulated, nonclinical environment
  • Multicentre (five university-affiliated anaesthesiology departments)
  • Blinded expert rating

Main finding

As reported in the abstract

Completeness

Domain-specific model

4.52

mean · SD 0.39

Anaesthesiologists

3.72

SD 0.43

General-purpose model

4.25

SD 0.48

P < 0.001

Observational data: associations, not effects.

Further findings

OutcomeDomain-specific model
Accuracymean 4.31 (SD 0.57)
Incomplete and inaccurate responses
Inaccurate answers1.3%
Accuracy — Accuracy did not differ significantly between groups; highest mean for the domain-specific model
P = 0.107

Inter-rater reliability

Inter-rater reliability range
0.717 to 0.885

Incomplete and inaccurate responses

Domain-specific model produced no incomplete responses

Parts of this Brief are withheld: the automatic checks could not confirm them against the abstract.

Original publication

Comparative performance of GPT-4 models and expert anaesthesiologists in peri-operative antithrombotic management: A cross-sectional evaluation. Eur J Anaesthesiol. Published 4 May 2026. doi:10.1097/eja.0000000000002418

Composed by AI from the published abstract and checked against it. How Briefs are made →

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