ArticleNPJ digital medicine2026
Randomised study of human machine collaboration for cardiotocography interpretation during labour.
Article in NPJ digital medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
7 authors.
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Abstract
Cardiotocography (CTG) interpretation during labour is subject to high interobserver variability, limiting its performance for predicting perinatal acidaemia. This study aimed to evaluate whether computerised CTG (cCTG) assistance improves clinicians' predictive performance. In a prospective randomised multi-reader design, 211 clinicians from 23 countries were proposed to assess 100 CTG recordings (50 with pH <7.15), with or without cCTG assistance. Participants predicted the occurrence of perinatal acidaemia. cCTG assistance significantly improved overall prediction, increasing the success rate from 54.0% to 61.4% (p < 0.01) and sensitivity from 49.3% to 61.7% (p < 0.01). There was no significant difference in specificity between groups (58.7% vs 61.2%, p = 0.14). In discordant cases, the cCTG model was correct 67.5% of the time. Agreement and reliability between clinicians were also improved across professions, countries and levels of experience. These findings suggest that cCTG enhances the detection of perinatal acidaemia.
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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 Socratic graph.