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Predictive value of traction force measurement in vacuum extraction: Development of a multivariate prognostic model.
- Source :
-
PLoS ONE . 3/3/2017, Vol. 12 Issue 3, p1-10. 10p. - Publication Year :
- 2017
-
Abstract
- 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—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. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 12
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- PLoS ONE
- Publication Type :
- Academic Journal
- Accession number :
- 121549526
- Full Text :
- https://doi.org/10.1371/journal.pone.0171938