Predictors of successful vaginal birth after a cesarean section in Ethiopia: a systematic review and meta-analysis

Mekonnen, Birye Dessalegn; Asfaw, Aragaw Awoke

doi:10.1186/s12884-023-05396-w

Cited by 3 publications

(2 citation statements)

References 44 publications

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“…Women with such a history may possess more favorable birth canals, thereby increasing the likelihood of a successful current vaginal delivery. 39 …”

Section: Discussionmentioning

confidence: 99%

Evaluating the performance of an AI-powered VBAC prediction system within a decision-aid birth choice platform for shared decision-making

Yang,

Wang,

Lin

et al. 2024

DIGITAL HEALTH

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Background Vaginal birth after cesarean (VBAC) is generally regarded as a safe and viable birthing option for most women with prior cesarean delivery. Nonetheless, concerns about heightened risks of adverse maternal and perinatal outcomes have often dissuaded women from considering VBAC. This study aimed to assess the performance of an artificial intelligence (AI)-powered VBAC prediction system integrated into a decision-aid birth choice platform for shared decision-making (SDM). Materials and Methods Employing a retrospective design, we collected medical records from a regional hospital in northern Taiwan from January 2019 to May 2023. To explore a suitable model for tabular data, we compared two prevailing modeling approaches: tree-based models and logistic regression models. We subjected the tree-based algorithm, CatBoost, to binary classification. Results Forty pregnant women with 347 records were included. The CatBoost model demonstrated a robust performance, boasting an accuracy rate of 0.91 (95% confidence interval (CI): 0.86–0.94) and an area under the curve of 0.89 (95% CI: 0.86–0.93), surpassing both regression models and other boosting techniques. CatBoost captured the data characteristics on the significant impact of gravidity and the positive influence of previous vaginal birth, reinforcing established clinical guidelines, as substantiated by the SHapley Additive exPlanations analysis. Conclusion Using AI techniques offers a more accurate assessment of VBAC risks, boosting women’s confidence in selecting VBAC as a viable birthing option. The seamless integration of AI prediction systems with SDM platforms holds a promising potential for enhancing the effectiveness of clinical applications in the domain of women's healthcare.

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“…Women with such a history may possess more favorable birth canals, thereby increasing the likelihood of a successful current vaginal delivery. 39 …”

Section: Discussionmentioning

confidence: 99%

Evaluating the performance of an AI-powered VBAC prediction system within a decision-aid birth choice platform for shared decision-making

Yang,

Wang,

Lin

et al. 2024

DIGITAL HEALTH

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“…Higher socioeconomic status has previously been associated with increased probability of failed trials of labor (Lehmann, et al, 2018). Further, results from studies in rural Ethiopia and Turkey have shown higher VBAC success rates in women from rural residences compared to urban setups (Mekonnen & Asfaw 2023;Senturk et al, 2015). Arguably, the reasons given for the observations range from preference of the women due fear of surgery, and affordability that may be due to socioeconomic status.…”

Section: Discussionmentioning

confidence: 99%

Outcomes of Trial of Labor after a Cesarean Section in Bomet County, Kenya

Ondego,

Otara,

Halestrap

et al. 2024

Kabarak j. res. innov.

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Trial of labor after cesarean section (TOLAC) is recommended for women with one prior cesarean section. However, TOLAC positive outcomes depend on selecting candidates to achieve higher success rates. Most available TOLAC data to inform patient selection originates from developed countries, which limits a patient-centered TOLAC practice in low-resource settings. Thus, we used a prospective observational cross-sectional approach to assess the success rate of TOLAC and establish the maternal and fetal factors associated with successful TOLAC in 170 women with one previous scar at two referral hospitals in Bomet County, a low-resource setting in Kenya. The primary maternal and neonatal outcomes were compared between those who had a vaginal birth after a cesarean section (VBAC) and those who had an emergency repeat cesarean section (ERCS) following a failed TOLAC between October 2022 and June 2023. The TOLAC success rate was 48.2% with the most common indication for emergency repeat cesarean section being failure to progress (34.1%). Factors associated with successful TOLAC included inter-delivery interval >60 months (p-0.044), and parity 2-4 (p- <0.001). Breech presentation and non-reassuring fetal status (NRFS) as indications for previous cesarean section, were associated with a successful VBAC (p-< 0.001, 0.033). In contrast, a birth weight of >3500 g was associated with an increased risk of ERCS. Moreover, a failed TOLAC was associated with a prolonged (>4 days) hospital stay (p-0.012). Our findings suggest that with proper patient selection, TOLAC remains a viable option with better outcomes if successful. However, TOLAC candidates should be evaluated based on the contextual factors of a given setting, hence careful patient selection is recommended to improve outcomes associated with TOLAC.

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Trend, prevalence and predictors of successful vaginal birth after caesarean section in Ethiopia: a systematic review and meta-analysis

Balis

Bekele

Hunde³

et al. 2023

International Health

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Background Vaginal birth after caesarean section (VBAC) is an alternative to a caesarean section (CS) in the absence of repeat or new indications for primary CS. There is a knowledge gap regarding the trend and successful VBAC in Ethiopia. Therefore this systematic review and meta-analysis aimed to assess the trend, pooled prevalence of successful VBAC and its predictors in Ethiopia. Methods Electronic databases (SCOPUS, CINAHL, Embase, PubMed and Web of Science), Google Scholar and lists of references were used to search works of literature in Ethiopia. Stata version 14 was used for analysis and the odds ratios of the outcome variable were determined using the random effects model. Heterogeneity among the studies was assessed by computing values for I2 and p-values. Also, sensitivity analyses and funnel plots were done to assess the stability of pooled values to outliers and publication bias, respectively. Results A total of 12 studies with a sample size of 2080 were included in this study. The overall success rate of VBAC was 52% (95% confidence interval 42 to 65). Cervical dilatation ≥4 cm at admission, having a prior successful vaginal delivery and VBAC were the predictors of successful VBAC. Conclusions Meta-analyses and sensitivity analyses showed the stability of the pooled odds ratios and the funnel plots did not show publication bias. The pooled prevalence of successful VBAC was relatively low compared with existing evidence. However, the rate was increasing over the last 3 decades, which implies it needs more strengthening and focus to decrease maternal morbidity and mortality by CS complications. Promoting VBAC by emphasizing factors favourable for its success during counselling mothers who previously delivered by CS to enhance the prevalence of VBAC.

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Predictors of successful vaginal birth after a cesarean section in Ethiopia: a systematic review and meta-analysis

Cited by 3 publications

References 44 publications

Evaluating the performance of an AI-powered VBAC prediction system within a decision-aid birth choice platform for shared decision-making

Evaluating the performance of an AI-powered VBAC prediction system within a decision-aid birth choice platform for shared decision-making

Outcomes of Trial of Labor after a Cesarean Section in Bomet County, Kenya

Trend, prevalence and predictors of successful vaginal birth after caesarean section in Ethiopia: a systematic review and meta-analysis

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