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Computerized data-driven interpretation of the intrapartum cardiotocogram: a cohort study.

Georgieva, A; Redman, CWG; Papageorghiou, AT (2017) Computerized data-driven interpretation of the intrapartum cardiotocogram: a cohort study. Acta Obstet Gynecol Scand, 96 (7). pp. 883-891. ISSN 1600-0412 https://doi.org/10.1111/aogs.13136
SGUL Authors: Papageorghiou, Aris

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Abstract

INTRODUCTION: Continuous intrapartum fetal monitoring remains a significant clinical challenge. We propose using cohorts of routinely collected data. We aim to combine non-classical (data-driven) and classical cardiotocography features with clinical features into a system (OxSys), which generates automated alarms for the fetus at risk of intrapartum hypoxia. We hypothesize that OxSys can outperform clinical diagnosis of "fetal distress", when optimized and tested over large retrospective data sets. MATERIAL AND METHODS: We studied a cohort of 22 790 women in labor (≥36 weeks of gestation). Paired umbilical blood analyses were available. Perinatal outcomes were defined by objective criteria (normal; severe, moderate or mild compromise). We used the data retrospectively to develop a prototype of OxSys, by relating its alarms to perinatal outcome, and comparing its performance against standards achieved by bedside diagnosis. RESULTS: OxSys1.5 triggers an alarm if the initial trace is nonreactive or the decelerative capacity (a nonclassical cardiotocography feature), exceeds a threshold, adjusted for preeclampsia and thick meconium. There were 187 newborns with severe, 613 with moderate and 3197 with mild compromise; and 18 793 with normal outcome. OxSys1.5 increased the sensitivity for compromise detection: 43.3% vs. 38.0% for severe (p = 0.3) and 36.1% vs. 31.0% for moderate (p = 0.06); and reduced the false-positive rate (14.4% vs. 16.3%, p < 0.001). CONCLUSIONS: Large historic cohorts can be used to develop and optimize computerized cardiotocography monitoring, combining clinical and cardiotocography risk factors. Our simple prototype has demonstrated the principle of using such data to trigger alarms, and compares well with clinical judgment.

Item Type: Article
Additional Information: This is the peer reviewed version of the following article: Georgieva, A, Redman, CWG, Papageorghiou, AT. Computerized data‐driven interpretation of the intrapartum cardiotocogram: a cohort study. Acta Obstet Gynecol Scand 2017; 96: 883– 891, which has been published in final form at https://doi.org/10.1111/aogs.13136. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
Keywords: Cardiotocography, computerized electronic fetal monitoring, intrapartum fetal monitoring, sensitivity, specificity, Cardiotocography, Cohort Studies, Decision Support Systems, Clinical, Diagnosis, Computer-Assisted, Female, Fetal Blood, Fetal Distress, Humans, Labor Presentation, Predictive Value of Tests, Pregnancy, Prenatal Care, Fetal Blood, Humans, Fetal Distress, Diagnosis, Computer-Assisted, Cardiotocography, Prenatal Care, Cohort Studies, Predictive Value of Tests, Pregnancy, Labor Presentation, Decision Support Systems, Clinical, Female, Cardiotocography, computerized electronic fetal monitoring, intrapartum fetal monitoring, sensitivity, specificity, Cardiotocography, computerized electronic fetal monitoring, intrapartum fetal monitoring, sensitivity, specificity, Cardiotocography, Cohort Studies, Decision Support Systems, Clinical, Diagnosis, Computer-Assisted, Female, Fetal Blood, Fetal Distress, Humans, Labor Presentation, Predictive Value of Tests, Pregnancy, Prenatal Care, Obstetrics & Reproductive Medicine, 1114 Paediatrics And Reproductive Medicine, 1117 Public Health And Health Services
SGUL Research Institute / Research Centre: Academic Structure > Institute of Medical & Biomedical Education (IMBE)
Academic Structure > Institute of Medical & Biomedical Education (IMBE) > Centre for Clinical Education (INMECE )
Journal or Publication Title: Acta Obstet Gynecol Scand
ISSN: 1600-0412
Language: eng
Dates:
DateEvent
20 June 2017Published
5 May 2017Published Online
19 March 2017Accepted
Publisher License: Publisher's own licence
Projects:
Project IDFunderFunder ID
UNSPECIFIEDAction Medical Researchhttp://dx.doi.org/10.13039/501100000317
UNSPECIFIEDHenry Smith Charityhttp://dx.doi.org/10.13039/501100000852
PubMed ID: 28369712
Web of Science ID: WOS:000403899400013
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/110954
Publisher's version: https://doi.org/10.1111/aogs.13136

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