A Prognostic Study for the Development of Risk Prediction Model for the Success of Vaginal Birth Following a Cesarean Surgery at Felege Hiwot Comprehensive Specialized Hospital, Northwest Ethiopia.

BACKGROUND

An attempt at vaginal delivery by a woman who has previously had a cesarean section is known as a trial of labor after cesarean section. The most important issues are how to accurately anticipate successful vaginal birth after cesarean surgery and how to calculate the likelihood of success of vaginal birth after caesarean section that is suitable for women. Consequently, a tailored prediction of vaginal birth after caesarean section may result in a more effective counseling.

OBJECTIVE

To create a clinical risk score and prediction model for the success of vaginal birth following a previous caesarean section in women.

METHODS

A prognostic analysis was carried out at Felege Hiwot Comprehensive and Specialized Referral Hospital from 30 February 2017 to 30 March 2021. R statistical programming language version 4.0 was used for analysis once the data had been coded and entered into Epidata, version 3.02. Significant factors (P< 0.05) were kept in the backward multivariable logistic regression model, and variables with (P<0.25) from the bi-variable logistic regression analysis were also added.

RESULTS

After a cesarean section, 67% of women were successful in giving birth vaginally. Previous successful vaginal birth after cesarean surgery, rupture of the membranes, and initiation time of ANC, the beginning of labor, parity and time since the previous delivery were remained in the final multivariable prediction model. The AUC of the model was 0.748 (95% CI: 0.714-0.781).

CONCLUSION

Overall, this study demonstrated the likelihood of predicting vaginal birth utilizing the ideal confluence of parity, membrane rupture, and onset of labor, prior history of VBAC, inter-delivery gap, and ANC beginning time. Sixty-seven percent of VBACs were successful. As a result, this model may aid in identifying pregnant women who are candidates for VBAC and who have a better likelihood of success.