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

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

OBJECTIVE

to analyze the temporal pattern and estimate mortality rates in the first 24 hours of life and from preventable causes in the state of Pernambuco from 2000 to 2021.

METHOD

an ecological study, using the quarter as the unit of analysis. The data source was made up of the Mortality Information System and the Live Birth Information System. The time series modeling was conducted according to the Autoregressive Integrated Moving Average Model.

RESULTS

14,462 deaths were recorded in the first 24 hours of life, 11,110 (76.8%) of which being preventable. It is observed from the forecasts that the mortality rate in the first 24 hours of life ranged from 3.3 to 2.4 per 1,000 live births, and the mortality rate from preventable causes ranged from 2.3 to 1.8 per 1,000 live births.

CONCLUSION

the prediction suggested progress in reducing mortality in the first 24 hours of life in the state and from preventable causes. The ARIMA models presented satisfactory estimates for mortality rates and preventable causes in the first 24 hours of life.

External validation of prediction models for vaginal delivery after the trial of labour among women with previous one caesarean section - A cohort study

OBJECTIVE

To externally validate three predictive models (the Grobman model (2007), the Zhang model (2020), and the Grobman model (2021)) for identifying women with increased chances of a successful trial of labour after caesarean section (TOLAC).

METHODS

This retrospective observational cohort study was conducted in a tertiary teaching hospital from 2018 to 2021. Individual probabilities were calculated for women with previous one caesarean section who underwent TOLAC at term, using the predicted probabilities from the logistic regression models. The primary outcome of this study was vaginal delivery following attempted TOLAC. The predictive ability of the models was assessed using the area under the receiver operative characteristics curves (AUC) and a calibration graph.

RESULTS

Of 1515 eligible women who underwent TOLAC, we found an overall rate of successful TOLAC of 60.3 %. No significant difference was noticed in adverse scar outcome and neonatal morbidity while comparing successful and failed TOLAC. The discriminative ability of Grobman-2007 and Grobman-2021 and the Zhang model were fair to poor with the AUC of 0.54(95 % CI 0.51-0.57), 0.62(95 % CI 0.59-0.65) and 0.66(95 % CI 0.63-0.69) respectively. The agreement between the observed rates of TOLAC success and the predicted probabilities for all three models was poor.

CONCLUSION

The performance of all three models predicting success after TOLAC was poor in the study population. A population-specific model may be needed, with the addition of factors influencing the labour, such as the methods of induction, which may aid in predicting the outcome.

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

OBJECTIVE

To validate the Maternal Fetal Medicine Unit's (MFMU) vaginal birth after cesarean delivery (VBAC) calculator in an Israeli cohort, and to detect other variables associated with VBAC and construct an improved VBAC calculator.

METHODS

A retrospective cohort study was performed at a single university-affiliated medical center. Women carrying a singleton, term, cephalic-presenting fetus, with previous one low transverse cesarean delivery who opted for trial of VBAC were included. Demographic and obstetric characteristics were incorporated into the MFMU's calculator, to predict probabilities of VBAC and compare prediction performance with the original publication utilizing receiver operating characteristic (ROC) statistics. Logistic regression analysis was used to investigate other variables and construct an improved model for success of VBAC.

RESULTS

Of 490 parturients, 396 (80.8%) had a successful vaginal delivery. Compared to the original publication, the MFMU's calculator underperformed: area under the ROC curve (AUC) was 0.709 (95% confidence interval [CI] 0.652-0.766, P < 0.001). Sensitivity, specificity, positive and negative predictive values, and overall accuracy were 67.42%, 65.96%, 89.30%, 32.46%, and 32.46%, respectively. An improved model that included previous VBAC, prior vaginal delivery, spontaneous onset of delivery, and maternal diabetes resulted in improved prediction performance with an AUC of 0.771 (95% CI 0.723-0.82, P < 0.001).

CONCLUSION

MFMU's VBAC calculator needs to be validated in different populations before implementation.