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Predictive value of traction force measurement in vacuum extraction: Development of a multivariate prognostic model
KTH, School of Technology and Health (STH).
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2017 (English)In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 12, no 3, e0171938Article in journal (Refereed) Published
Abstract [en]

Objective To enable early prediction of strong traction force vacuum extraction. Design Observational cohort. Setting Karolinska University Hospital delivery ward, tertiary unit. Population and sample size Term mid and low metal cup vacuum extraction deliveries June 2012 D February 2015, n = 277. Methods Traction forces during vacuum extraction were collected prospectively using an intelligent handle. Levels of traction force were analysed pairwise by subjective category strong versus non-strong extraction, in order to define an objective predictive value for strong extraction. Statistical analysis A logistic regression model based on the shrinkage and selection method lasso was used to identify the predictive capacity of the different traction force variables. Predictors Total (time force integral, Newton minutes) and peak traction (Newton) force in the first to third pull; difference in traction force between the second and first pull, as well as the third and first pull respectively. Accumulated traction force at the second and third pull. Outcome Subjectively categorized extraction as strong versus non-strong. Results The prevalence of strong extraction was 26%. Prediction including the first and second pull: AUC 0,85 (CI 0,80-0,90); specificity 0,76; sensitivity 0,87; PPV 0,56; NPV 0,94. Prediction including the first to third pull: AUC 0,86 (CI 0,80-0,91); specificity 0,87; sensitivity 0,70; PPV 0,65; NPV 0,89. Conclusion Traction force measurement during vacuum extraction can help exclude strong category extraction from the second pull. From the third pull, two-thirds of strong extractions can be predicted.

Place, publisher, year, edition, pages
PUBLIC LIBRARY SCIENCE , 2017. Vol. 12, no 3, e0171938
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Medical and Health Sciences
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URN: urn:nbn:se:kth:diva-204055DOI: 10.1371/journal.pone.0171938ISI: 000396021100010PubMedID: 28257459Scopus ID: 2-s2.0-85014429628OAI: oai:DiVA.org:kth-204055DiVA: diva2:1085739
Note

QC 20170330

Available from: 2017-03-30 Created: 2017-03-30 Last updated: 2017-03-30Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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