External validation of a prediction model on vaginal birth after caesarean in a The Netherlands: a prospective cohort study

Abstract

ObjectivesDiscussing the individual probability of a successful vaginal birth after caesarean (VBAC) can support decision making. The aim of this study is to externally validate a prediction model for the probability of a VBAC in a Dutch population.MethodsIn this prospective cohort study in 12 Dutch hospitals, 586 women intending VBAC were included. Inclusion criteria were singleton pregnancies with a cephalic foetal presentation, delivery after 37 weeks and one previous caesarean section (CS) and preference for intending VBAC. The studied prediction model included six predictors: pre-pregnancy body mass index, previous vaginal delivery, previous CS because of non-progressive labour, Caucasian ethnicity, induction of current labour, and estimated foetal weight ≥90th percentile. The discriminative and predictive performance of the model was assessed using receiver operating characteristic curve analysis and calibration plots.ResultsThe area under the curve was 0.73 (CI 0.69–0.78). The average predicted probability of a VBAC according to the prediction model was 70.3% (range 33–92%). The actual VBAC rate was 71.7%. The calibration plot shows some overestimation for low probabilities of VBAC and an underestimation of high probabilities.ConclusionsThe prediction model showed good performance and was externally validated in a Dutch population. Hence it can be implemented as part of counselling for mode of delivery in women choosing between intended VBAC or planned CS after previous CS.

Temporal analysis of mortality from preventable causes in the first 24 hours of life, 2000-2021

“…As an example of the use of the ARIMA modeling, a study evaluated the performance of some states on infant mortality and showed that the method was satisfactory in its predictions, showing that some states would not be able to reach the 2017 national policy target of 29 deaths per 1,000 live births by 2019 ( 48 ) . In this way, forecasting methods can be applied to transform care practices and direct the development of public health policies ( 52 ) , in addition to being a methodology that allows the use of data from official sources and low operational costs ( 53 ) .…”

“…The use of this type of modeling in the decision-making and health policy-making process in poorer countries is still a challenge, whether due to the absence or fragility of the systematic collection of epidemiological data, or the difficulty of consolidating quality information systems and establishing a culture of data usage ( 53 ) .…”

Análisis temporal de la mortalidad por causas evitables en las primeras 24 horas de vida, 2000-2021

“…Como ejemplo del uso del modelado ARIMA, un estudio evaluó el desempeño de algunos estados sobre la mortalidad infantil y mostró que el método fue satisfactorio (48) . Así, los métodos de pronóstico pueden ser aplicados para transformar las prácticas asistenciales y direccionar la elaboración de políticas públicas de salud (52) , además de ser una metodología que permite utilizar datos de fuentes oficiales y de bajo costo operacional (53) .…”

“…El uso de este tipo de modelaje en el proceso decisorio y formulador de políticas en salud en los países más pobres aún es un desafío, ya sea por la ausencia o fragilidad en la recogida sistemática de datos epidemiológicos, o por la dificultad de consolidar sistemas de información de calidad e instaurar una cultura de utilización de datos (53) .…”

External validation of vaginal birth after cesarean delivery calculator in Israeli cohort of parturients and construction of an improved model

“…The authors further created a graphic normogram and an easy-touse online calculator that can predict individual chances for successful TOLAC. Following its publication, studies tried to validate the MFMU's calculator in different populations and settings [9][10][11][12][13][14] with conflicting results.…”