title: Predictive value of traction force measurement in vacuum extraction: Development of a multivariate prognostic model.
abstract: OBJECTIVE
  To enable early prediction of strong traction force vacuum extraction.
  
  
  METHODS
  Observational cohort.
  
  
  METHODS
  Karolinska University Hospital delivery ward, tertiary unit.
  
  
  METHODS
  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.
  
  
  METHODS
  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.
  
  
  METHODS
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Obstetrics and gynecology, Karolinska University Hospital, Stockholm, Sweden.|Clintec, Karolinska Institute, Stockholm, Sweden.
authors.forename: Kristina
authors.initials: K
authors.lastname: Pettersson
authors.affiliation: Clintec, Karolinska Institute, Stockholm, Sweden.|School of Technology and Health, Royal Institute of Technology, Stockholm, Sweden.
authors.forename: Khurram
authors.initials: K
authors.lastname: Yousaf
authors.affiliation: Statistician, Swedish Patient Insurance, Stockholm, Sweden.
authors.forename: Jonas
authors.initials: J
authors.lastname: Ranstam
authors.affiliation: Obstetrics and gynecology, Karolinska University Hospital, Stockholm, Sweden.|Clintec, Karolinska Institute, Stockholm, Sweden.
authors.forename: Magnus
authors.initials: M
authors.lastname: Westgren
authors.affiliation: Obstetrics and gynecology, Karolinska University Hospital, Stockholm, Sweden.|Clintec, Karolinska Institute, Stockholm, Sweden.
authors.forename: Gunilla
authors.initials: G
authors.lastname: Ajne
mesh_terms: D000293:Adolescent; D000328:Adult; D001720:Birth Injuries / Q000503:physiopathology*; D004864:Equipment and Supplies / Q000009:adverse effects; D005260:Female; D006470:Hemorrhage / Q000503:physiopathology*; D006801:Humans; D055595:Mechanical Phenomena; D011247:Pregnancy; D011379:Prognosis; D014620:Vacuum Extraction, Obstetrical / Q000009:adverse effects / Q000379:methods*