PloS one · 2017
Predictive value of traction force measurement in vacuum extraction: Development of a multivariate prognostic model.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Pettersson Kristina, Yousaf Khurram, Ranstam Jonas, Westgren Magnus, Ajne Gunilla
Аннотация
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.
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.