Evidence mapPaperPMID 41857310Full record

ArticleNPJ digital medicine2026

Randomised study of human machine collaboration for cardiotocography interpretation during labour.

Imane Ben M'Barek, Badr Ben M'Barek, Grégoire Jauvion, Virginia Whelehan, Aris Papageorghiou, Erwan Le Pennec, Julien Stirnemann

Abstract read
In one paragraph

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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0cells of the map it votes in
0citing papers in PubMed
field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Imane Ben M'BarekDepartment of Obstetrics and Gynaecology, Assistance Publique des Hôpitaux de Paris-Beaujon, Clichy, France. imane.benmbarek@aphp.fr.
Badr Ben M'BarekGenos Care, Paris, France.
Grégoire JauvionGenos Care, Paris, France.
Virginia WhelehanDepartment of Obstetrics and Gynaecology, St George's University Hospitals NHS Foundation Trust, London, UK.
Aris PapageorghiouDepartment of Obstetrics and Gynaecology, St George's University Hospitals NHS Foundation Trust, London, UK.
Erwan Le PennecCMAP, CNRS, Ecole Polytechnique, Institut Polytechnique de Paris, Palaiseau, France.
Julien StirnemannUniversité Paris Cité & Institut IMAGINE, Paris, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID41857310
PMCPMC13168585

What Socratic holds

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Registered trials

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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.