ArticleBritish journal of anaesthesia2025
Generative AI models: the next anaesthetic agent?
Article in British journal of anaesthesia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Artificial intelligence in perioperative pressure injury management: a scoping review of evidence, gaps, and implications for population health and digital public health policy.Frontiers in public health · 2026Pooled it
- Effectiveness of an artificial intelligence-assisted training program on cleaning competency among hospital environmental service staff.BMC health services research · 2026Trial
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A study by MacKay and colleagues addresses a pressing need in cardiac anaesthesia by demonstrating an innovative method to extract structured data from free-text intraoperative transoesophageal echocardiography reports. Narrative descriptions of echocardiographic findings are often unstructured, making manual extraction labour-intensive and susceptible to error. By deploying an ensemble of large language models in a consensus-based framework, the authors show that key echocardiographic parameters can be extracted with a high degree of accuracy and manageable error rates. This work presents a technical solution to a specific data-handling challenge and points towards broader applications of artificial intelligence (AI) in streamlining perioperative care.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.