A Performance Evaluation of Computerised Antepartum Fetal Heart Rate Monitoring: The Dawes-Redman Algorithm at Term

Objectives: This study aims to rigorously evaluate the Dawes-Redman computerised cardiotocography algorithm's effectiveness in assessing antepartum fetal wellbeing. It focuses on analysing the algorithm's performance using extensive clinical data, examining accuracy, sensitivity, specificity, and predictive values in various scenarios. The objectives include assessing the algorithm's reliability in identifying fetal wellbeing across different risk prevalences, its efficacy in the context of temporal proximity to delivery, and its performance across ten specific adverse pregnancy outcomes. This comprehensive evaluation seeks to clarify the algorithm's utility and limitations in contemporary obstetric practice, particularly in high-risk pregnancy scenarios. Methods: Antepartum fetal heart rate recordings from term singleton pregnancies between 37 and 42 gestational weeks were extracted from the Oxford University Hospitals database, spanning 1991 to 2021. Traces with significant data gaps or incomplete Dawes-Redman analyses were excluded. For the ten adverse outcomes, only traces performed within 48 hours prior to delivery were considered, aligning with clinical decision-making practices. A healthy cohort was established using rigorous inclusion and exclusion criteria based on clinical indicators. Propensity score matching, controlling for gestational age and fetal sex, ensured balanced comparisons between healthy and adverse outcome cohorts. The Dawes-Redman algorithm's categorisation of FHR traces as either 'criteria met' (an indicator of wellbeing) or 'criteria not met' (indicating a need for further evaluation) informed the evaluation of predictive performance metrics. Performance was assessed using accuracy, sensitivity, specificity, and predictive values (PPV, NPV), adjusted for various risk prevalences. Results: 4,196 term antepartum FHR traces were identified, matched by fetal sex and gestational age. The Dawes-Redman algorithm showed a high sensitivity of 91.7% for detecting fetal wellbeing. However, specificity for adverse outcomes was low at 15.6%. The PPV varied with population prevalence, high in very low-risk settings (99.1%) and declined with increased risk. Temporal proximity to delivery indicated robust sensitivity (>91.0%). Specificity notably decreased over time, impacting the algorithm's discriminative power for identifying adverse outcomes. Across different adverse conditions, the algorithm's performance remained consistent, with high sensitivity but varying NPVs, confirming its utility in detecting fetal wellbeing rather than adverse outcomes. Conclusion: These findings reveal the Dawes-Redman algorithm is effective for detecting fetal wellbeing in term pregnancies, evidenced by its high sensitivity and PPV. However, its low specificity suggests limitations in its ability to identify fetuses at risk of adverse outcomes. The predictive accuracy of the algorithm is significantly affected by the prevalence of healthy pregnancies within the population. Clinical interpretation of FHR traces that do not satisfy the Dawes-Redman criteria should be approached with caution, as they do not necessarily correlate with heightened risk. While the algorithm proves reliable for its primary objective in low-risk contexts, the development of algorithms optimised for high-risk pregnancy scenarios remains an area for future enhancement. ### Competing Interest Statement All authors have completed the Unified Competing Interest form (available on request from the corresponding author) and declare: no support from any organisation for the submitted work; Huntleigh Healthcare provides financial support for educational services provided by BA, however no other author receives any financial benefit. No other relationships or activities that could appear to have influenced the submitted work. ### Funding Statement This study was not supported by any external funding. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study was approved by the Ethics Committee in Joint Research Office, Research and Development Department, Oxford University Hospitals NHS Trust: 13/SC/0153. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The authors acknowledge the importance of data transparency and the potential value of data sharing in advancing scientific research. However, due to the identifiable and sensitive nature of the data used in this study, which includes detailed fetal heart rate traces potentially linked to individual patient outcomes, we are unable to make the dataset publicly available. The data contains protected health information and is subject to strict confidentiality constraints to safeguard the privacy of individuals. Consequently, the ethical and legal restrictions prevent the sharing of the dataset.