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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
  • Hôpital Beaujon
  • Laboratoire de Probabilités et Modèles Aléatoires
  • Genos Care
  • St George’s University Hospitals NHS Foundation Trust
  • University of Oxford Medical Sciences Division
  • Groupe Hospitalier Lariboisiere-Fernand Widal Assistance Publique-Hopitaux de Paris (AP-HP)

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number365
Journalnpj Digital Medicine
Volume9
Issue number1
DOIs
Publication statusPublished - 1 Dec 2026

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