**Conflict of interest**

*Recent Advances in Cesarean Delivery*

women.

study populations.

**4. Conclusions**

caesarean delivery.

event of cephalo-pelvic disproportion.

making and birth planning.

had delivered a baby >4000 g.

predictors identified and the authors concluded that this could be of benefit in assisting decision-making around the most appropriate mode of delivery for

This study was designed as a prospective observational study with a sample size of 453 women. However, it should be noted that the authors did not consider examine BMI as a potential predictor. This has been shown by many studies in the literature, some of which have already been mentioned [98, 123] in this literature review as being highly predictive for intrapartum Caesarean delivery. The authors also cautioned that the predictive performance of the model might be overstated as its measures of discrimination are derived from the same analysis that was used to derive the model. They recommended further studies to validate this model in other

Mazouni et al. also developed and validated a nomogram to predict the risk of Caesarean delivery in macrosomic infants [124]. This was developed using the data collated from 246 women initially and validated in a further study of 206 women in Marseille, France. Interestingly, this study also included multiparous women. The final key predictors, which were incorporated into the nomogram, were: maternal age (p = 0.01), maternal height (p = 0.02), parity (p < 0.001), and previous Caesarean section (p = 0.009). This study did not examine any ultrasonographic details and instead it retrospectively examined the maternal data of women who

Burke et al. published in 2017 a similar conjugate model [125] that represents the predecessor for the subject of this thesis. The genesis study was a prospective observational study, which recruited 2336 low-risk nulliparous women from the island of Ireland from October 2012 to June 2015. These women attended for ultrasound assessment and collection of maternal anthropometric data from 38 + 0 weeks of pregnancy until 40 + 6 weeks of pregnancy and their delivery outcomes were later collated. Genesis found that five parameters were noted to be the most significant predictors of risk of a nulliparous women undergoing intrapartum Caesarean section delivery. These 5 parameters were advancing maternal age OR, 1.21 (95% confidence interval [CI], 1.09–1.34), P = .0005; increasing maternal BMI OR, 1.29 (95% CI, 1.17–1.42), P < 0.0001; shorter maternal height OR, 1.72 (95% CI, 1.54–1.92), P < 0.0001; larger foetal HC OR, 1.27 (95% CI, 1.13–1.42), P = 0.0001;

These five predictors were then used to develop a nomogram to individually calculate each nulliparous woman's risk for requiring intrapartum Caesarean delivery.

We have highlighted the benefits of risk prediction models in many aspects of healthcare. We know from our own reading that these models have been developed in the field of obstetrics and particularly with the interest of predicting intrapartum

However, we are still awaiting a validated successful model, which may be used in clinical practice. We have also not identified any research studies examining the usage of Artificial Intelligence to aid with risk prediction or any randomised trials reviewing the merits of elective Caesarean delivery versus trial of labour in the

A focus group amongst expectant first-time mothers in our unit confirmed that women would be keen on the introduction of a risk predictive tool, which would be individualised for each woman. They felt that this would aid them in their decision-

and larger foetal AC OR, 1.23 (95% CI, 1.1–1.37) P = .0004.

**14**

The authors declare no conflict of interest.
