Blinded ultrasound fetal biometry at 36 weeks and risk of emergency Cesarean delivery in a prospective cohort study of low-risk nulliparous women

Fetal and Maternal Factors Predictive of Primary Cesarean Delivery at Term in a Low-Risk Population: NICHD Fetal Growth Studies-Singletons

OBJECTIVE

 This study aimed to examine associations of fetal biometric and amniotic fluid measures with intrapartum primary cesarean delivery (PCD) and develop prediction models for PCD based on ultrasound parameters and maternal factors.

STUDY DESIGN

 Secondary analysis of the National Institute of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-singleton cohort (2009-2013) including patients with uncomplicated pregnancies and intent to deliver vaginally at ≥370/7 weeks. The estimated fetal weight, individual biometric parameters, fetal asymmetry measurements, and amniotic fluid single deepest vertical pocket assessed at the final scan (mean 37.5 ± 1.9 weeks) were categorized as <10th, 10th to 90th (reference), and >90th percentiles. Logistic regression analyses examined the association between the ultrasound measures and PCD. Fetal and maternal SuperLearner prediction algorithms were constructed for the full and nulliparous cohorts.

RESULTS

 Of the 1,668 patients analyzed, 249 (14.9%) had PCD. The fetal head circumference, occipital-frontal diameter, and transverse abdominal diameter >90th percentile (adjusted odds ratio [aOR] = 2.50, 95% confidence interval [95% CI]: 1.39, 4.51; aOR = 1.86, 95% CI: 1.02, 3.40; and aOR = 2.13, 95% CI: 1.16, 3.89, respectively) were associated with PCD. The fetal model demonstrated poor ability to predict PCD in the full cohort and in nulliparous patients (area under the receiver-operating characteristic curve [AUC] = 0.56, 95% CI: 0.52, 0.61; and AUC = 0.54, 95% CI: 0.49, 0.60, respectively). Conversely, the maternal model had better predictive capability overall (AUC = 0.79, 95% CI: 0.75, 0.82) and in the nulliparous subgroup (AUC = 0.72, 95% CI: 0.67, 0.77). Models combining maternal/fetal factors performed similarly to the maternal model (AUC = 0.78, 95% CI: 0.75, 0.82 in full cohort, and AUC = 0.71, 95% CI: 0.66, 0.76 in nulliparas).

CONCLUSION

 Although a few fetal biometric parameters were associated with PCD, the fetal prediction model had low performance. In contrast, the maternal model had a fair-to-good ability to predict PCD.

KEY POINTS

· Fetal HC >90th percentile was associated with cesarean delivery.. · Fetal parameters did not effectively predict PCD.. · Maternal factors were more predictive of PCD.. · Maternal/fetal and maternal models performed similarly.. · Prediction models had lower performance in nulliparas..

Ensemble learning for fetal ultrasound and maternal-fetal data to predict mode of delivery after labor induction

Providing adequate counseling on mode of delivery after induction of labor (IOL) is of utmost importance. Various AI algorithms have been developed for this purpose, but rely on maternal-fetal data, not including ultrasound (US) imaging. We used retrospectively collected clinical data from 808 subjects submitted to IOL, totaling 2024 US images, to train AI models to predict vaginal delivery (VD) and cesarean section (CS) outcomes after IOL. The best overall model used only clinical data (F1-score: 0.736; positive predictive value (PPV): 0.734). The imaging models employed fetal head, abdomen and femur US images, showing limited discriminative results. The best model used femur images (F1-score: 0.594; PPV: 0.580). Consequently, we constructed ensemble models to test whether US imaging could enhance the clinical data model. The best ensemble model included clinical data and US femur images (F1-score: 0.689; PPV: 0.693), presenting a false positive and false negative interesting trade-off. The model accurately predicted CS on 4 additional cases, despite misclassifying 20 additional VD, resulting in a 6.0% decrease in average accuracy compared to the clinical data model. Hence, integrating US imaging into the latter model can be a new development in assisting mode of delivery counseling.

Nomogram based on the final antepartum ultrasound features before delivery for predicting failed spontaneous vaginal delivery in nulliparous women

Background

Accurate identification of nulliparous women with failed spontaneous vaginal delivery (SVD) is crucial to minimize the hazards associated with obstetrical intervention (OI). While abnormal labor progression can be identified with intrapartum ultrasonography, labor-related complications may be unavoidable due to the limited time window left to the obstetrician. Antepartum ultrasound enables sufficient obstetric planning. However, there is typically a longer gap between ultrasound assessment and delivery that often lowers the prediction accuracy compared to intrapartum ultrasonography.

Objective

In this study, antepartum ultrasound assessment was included to each fetal ultrasound examination after 36 weeks of gestation until the onset of labor. We aim to establish a nomogram to predict the likelihood of failed SVD in nulliparous women using the last antepartum ultrasound findings before labor beginning.

Methods

Of the 2,143 nulliparous women recruited, 1,373 were included in a training cohort and 770 in a validation cohort, based on their delivery date. Maternal and perinatal characteristics, as well as perinatal ultrasound parameters were collected. In the training cohort, the screened correlates of SVD failure were used to develop a nomogram for determining whether a nulliparous woman would experience SVD failure. This model was validated in both training and validation cohorts.

Results

SVD failure affected 217 nulliparous women (10.13%). In the training cohort, SVD failure was independently associated with BMI [odds ratio (OR) = 1.636], FHC (OR = 1.194), CL (OR = 1.398), and PCA (OR = 0.824) (all P < 0.05). They constituted a nomogram to estimate the individual risk of SVD failure. The model obtained clinical net benefits in both the training and validation cohorts and was validated to present strong discrimination and calibration.

Conclusion

The developed nomogram based on the last antepartum ultrasound findings may be helpful in avoiding OI and its related complications by assessing the likelihood of a failed SVD in nulliparous women.

An intrapartum calculator for predicting cesarean birth due to dystocia: Preliminary findings from a single-center study in Korea

BACKGROUND

Previous calculators based on antepartum or pre-labor factors preclude intrapartum counseling. We aimed to develop a reliable, programmable, intrapartum calculator to predict the risk of cesarean birth (CB) due to dystocia and to increase the discriminatory accuracy of the predictive model.

METHODS

Data were obtained retrospectively for 1326 singleton term deliveries with cephalic presentation. Two predictive multivariable logistic regression analysis models were constructed using pre-active labor variables alone (model A) or with active labor variables (model B). The discriminatory accuracies and goodness-of-fit of the models were compared using receiver operating characteristic (ROC) curves or -2log-likelihood ratios, Akaike information criterion (AIC), and Bayesian information criterion (BIC), respectively. Both models were internally validated using a bootstrapping procedure.

RESULTS

Model A yielded an area under the curve (AUC) of 0.859 and adequate goodness of fit (P = 0.970). Model B yielded a significantly higher AUC of 0.887 and adequate goodness of fit (P = 0.624), as well as a significantly lower AIC and BIC (P &lt; 0.001). Internal validation revealed a minimal optimism of 0.0070491 and 0.0068976 for models A and B, respectively. Finally, the logistic regression equations were converted into programmable calculators to yield easy-to-understand basic (model A) and additional intrapartum CB calculators (model B).

CONCLUSIONS

The programmable calculators developed herein can augment intrapartum counseling. Our findings suggest that the risk of CB due to dystocia during labor should be estimated using a calculator that corresponds to labor progression. Further studies should explore external validation of these statistical models before translation to a clinical setting.

Comparison of Multivariable Logistic Regression and Other Machine Learning Algorithms for Prognostic Prediction Studies in Pregnancy Care: Systematic Review and Meta-Analysis

BACKGROUND

Predictions in pregnancy care are complex because of interactions among multiple factors. Hence, pregnancy outcomes are not easily predicted by a single predictor using only one algorithm or modeling method.

OBJECTIVE

This study aims to review and compare the predictive performances between logistic regression (LR) and other machine learning algorithms for developing or validating a multivariable prognostic prediction model for pregnancy care to inform clinicians' decision making.

METHODS

Research articles from MEDLINE, Scopus, Web of Science, and Google Scholar were reviewed following several guidelines for a prognostic prediction study, including a risk of bias (ROB) assessment. We report the results based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Studies were primarily framed as PICOTS (population, index, comparator, outcomes, timing, and setting): Population: men or women in procreative management, pregnant women, and fetuses or newborns; Index: multivariable prognostic prediction models using non-LR algorithms for risk classification to inform clinicians' decision making; Comparator: the models applying an LR; Outcomes: pregnancy-related outcomes of procreation or pregnancy outcomes for pregnant women and fetuses or newborns; Timing: pre-, inter-, and peripregnancy periods (predictors), at the pregnancy, delivery, and either puerperal or neonatal period (outcome), and either short- or long-term prognoses (time interval); and Setting: primary care or hospital. The results were synthesized by reporting study characteristics and ROBs and by random effects modeling of the difference of the logit area under the receiver operating characteristic curve of each non-LR model compared with the LR model for the same pregnancy outcomes. We also reported between-study heterogeneity by using τ2 and I2.

RESULTS

Of the 2093 records, we included 142 studies for the systematic review and 62 studies for a meta-analysis. Most prediction models used LR (92/142, 64.8%) and artificial neural networks (20/142, 14.1%) among non-LR algorithms. Only 16.9% (24/142) of studies had a low ROB. A total of 2 non-LR algorithms from low ROB studies significantly outperformed LR. The first algorithm was a random forest for preterm delivery (logit AUROC 2.51, 95% CI 1.49-3.53; I2=86%; τ2=0.77) and pre-eclampsia (logit AUROC 1.2, 95% CI 0.72-1.67; I2=75%; τ2=0.09). The second algorithm was gradient boosting for cesarean section (logit AUROC 2.26, 95% CI 1.39-3.13; I2=75%; τ2=0.43) and gestational diabetes (logit AUROC 1.03, 95% CI 0.69-1.37; I2=83%; τ2=0.07).

CONCLUSIONS

Prediction models with the best performances across studies were not necessarily those that used LR but also used random forest and gradient boosting that also performed well. We recommend a reanalysis of existing LR models for several pregnancy outcomes by comparing them with those algorithms that apply standard guidelines.

TRIAL REGISTRATION

PROSPERO (International Prospective Register of Systematic Reviews) CRD42019136106; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=136106.

Cesarean section and childhood infections: Causality for concern?

In this Perspective, Gordon Smith discusses the findings of Miller et al, and the balance of risks and benefits associated with different modes of delivery.

Maternal cardiovascular function and risk of intrapartum fetal compromise in women undergoing induction of labor: pilot study

OBJECTIVE

Identification of the fetus at risk of intrapartum compromise has many benefits. Impaired maternal cardiovascular function is associated with placental hypoperfusion predisposing to intrapartum fetal distress. The aim of this study was to assess the predictive accuracy of maternal hemodynamics for the risk of operative delivery due to presumed fetal compromise in women undergoing induction of labor (IOL).

METHODS

In this prospective cohort study, patients were recruited between November 2018 and January 2019. Women undergoing IOL were invited to participate in the study. A non-invasive ultrasonic cardiac output monitor (USCOM-1A®) was used for cardiovascular assessment. The study outcome was operative delivery due to presumed fetal compromise, which included Cesarean or instrumental delivery for abnormal fetal heart monitoring. Regression analysis was used to test the association between cardiovascular markers, as well as the maternal characteristics, and the risk of operative delivery due to presumed fetal compromise. Receiver-operating-characteristics-curve analysis was used to assess the predictive accuracy of the cardiovascular markers for the risk of operative delivery for presumed fetal compromise.

RESULTS

A total of 99 women were recruited, however four women were later excluded from the analysis due to semi-elective Cesarean section (n = 2) and failed IOL (n = 2). The rate of operative delivery due to presumed fetal compromise was 28.4% (27/95). Women who delivered without suspected fetal compromise (controls) were more likely to be parous, compared to those who had operative delivery due to fetal compromise (52.9% vs 18.5%; P = 0.002). Women who underwent operative delivery due to presumed fetal compromise had a significantly lower cardiac index (median, 2.50 vs 2.60 L/min/m² ; P = 0.039) and a higher systemic vascular resistance (SVR) (median, 1480 vs 1325 dynes × s/cm⁵ , P = 0.044) compared to controls. The baseline model (being parous only) showed poor predictive accuracy, with an area under the curve of 0.67 (95% CI, 0.58-0.77). The addition of stroke volume index (SVI) < 36 mL/m² , SVR > 7.2 logs or SVR index (SVRI) > 7.7 logs improved significantly the predictive accuracy of the baseline model (P = 0.012, P = 0.026 and P = 0.012, respectively).

CONCLUSION

In this pilot study, we demonstrated that prelabor maternal cardiovascular assessment in women undergoing IOL could be useful for assessing the risk of intrapartum fetal compromise necessitating operative delivery. The addition of SVI, SVR or SVRI improved significantly the predictive accuracy of the baseline antenatal model. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.

Caesarean sections are associated with sonographic determined fetal size from the second trimester onwards

Human birth represents a critical and life-threatening event in the life of mother and child and is therefore of special importance for anthropological as well as public health research.

Study aims: to analyze the association patterns between fetal biometry and delivery modes from the first trimester onwards.

In this electronic medical record-based study, a dataset of 3408 singleton term birth taking place at the Viennese Danube hospital in Austria. was analyzed. Fetal biometry was reconstructed by the results of three ultrasound examinations carried out at the 11th/12th, 20th/21th and 32th/33thweek of gestation. In detail, crown-rump length, biparietal diameter, fronto-occipital diameter, head circumference, abdominal trans-verse diameter, abdominal sagittal diameter, abdominal circumference, and femur length were determined. Birth weight, birth length and head circumference were measured immediately after birth. Four delivery modes were compared: spontaneous vaginal birth, instrumental vaginal birth, planned cesarean section and emergency cesarean section.

The total cesarean section rate was 10.2%. Fetal biometry and newborn size differed significantly between the four delivery modes. From the second trimester onward, head circumferences were significantly larger (p=0.005) among fetuses delivered by instrumental delivery or emergency cesarean section than among fetuses delivered by spontaneous vaginal birth. The fetal abdominal dimensions during the third trimester were significantly largest (p=0.001) among fetuses delivered by emergency cesarean section. In comparison to spontaneous vaginal delivery the risk to require instrumental delivery increased significantly with increasing fetal head dimensions at the second (p=0.019) and third trimester(p=0.032) independent of maternal somatic factors. The risk of emergency CS increased significantly with increasing head dimensions (p=0.030) as well as abdominal dimensions (p=0.001) at the third trimester and newborn size (p=0.002), also independently of maternal somatic factors.

In general, larger fetuses are on an increased risk of experiencing instrumental delivery or emergency caesarean section. This association between fetal size and delivery mode is detectable from the second trimester onwards.

Ultrasound in labor admission to predict need for emergency cesarean section: a prospective, blinded cohort study

OBJECTIVE

To assess whether assessment with ultrasound could improve the detection of emergency cesarean section (ECS) in laboring women.

METHODS

Women who presented with symptoms of active labor or women in need of labor induction were invited to participate in the study. Women included in the study were evaluated with ultrasonography for fetal biometry and vaginal examinations for Bishop score assessment. The main aim in this study was determining factors associated with ECS due to fetal distress and obstructed labor.

RESULTS

No fetal biometry variable was associated with ECS due to any indication (fetal distress and obstructed labor combined) in the univariate analysis. In multivariate analyses, biometry variables were adjusted for Bishop score at admission and only abdominal circumference percentile showed a significant association with the odds of ECS due to any indication (OR:1.02, 95% CI: 1.01-1.03). Biparietal diameter and abdominal circumference variables were associated with the odds of ECS due to obstructed labor in both univariate and multivariate analyses (p < .05 for all). However, the predictive accuracy of biparietal diameter percentile (area under the curve (AUC): 0.55, 95% CI: 0.46-0.63) and abdominal circumference percentile (AUC: 0.56, 95% CI: 0.48-0.64) without adjunct variables were poor. Moreover, the addition of fetal biometry parameters to Bishop score did not improve the predictive accuracy of Bishop score.

CONCLUSION

Ultrasound assessment at admission, in addition to Bishop score assessment, did not significantly improve the prediction of ECS. Also, the fetal biometry alone had poor predictive capability for ECS. Routine ultrasound assessment at labor admission appears to be ineffective for predicting ECS.PrecisFetal biparietal diameter and abdominal circumference showed an association with emergency cesarean due to obstructed labor but the predictive accuracy of fetal biometry was low. Routine ultrasound examination at admission, in addition to Bishop score assessment, may not useful for assessing the risk of emergency section in unselected populations.

Screening for breech presentation using universal late-pregnancy ultrasonography: A prospective cohort study and cost effectiveness analysis

BACKGROUND

Despite the relative ease with which breech presentation can be identified through ultrasound screening, the assessment of foetal presentation at term is often based on clinical examination only. Due to limitations in this approach, many women present in labour with an undiagnosed breech presentation, with increased risk of foetal morbidity and mortality. This study sought to determine the cost effectiveness of universal ultrasound scanning for breech presentation near term (36 weeks of gestational age [wkGA]) in nulliparous women.

METHODS AND FINDINGS

The Pregnancy Outcome Prediction (POP) study was a prospective cohort study between January 14, 2008 and July 31, 2012, including 3,879 nulliparous women who attended for a research screening ultrasound examination at 36 wkGA. Foetal presentation was assessed and compared for the groups with and without a clinically indicated ultrasound. Where breech presentation was detected, an external cephalic version (ECV) was routinely offered. If the ECV was unsuccessful or not performed, the women were offered either planned cesarean section at 39 weeks or attempted vaginal breech delivery. To compare the likelihood of different mode of deliveries and associated long-term health outcomes for universal ultrasound to current practice, a probabilistic economic simulation model was constructed. Parameter values were obtained from the POP study, and costs were mainly obtained from the English National Health Service (NHS). One hundred seventy-nine out of 3,879 women (4.6%) were diagnosed with breech presentation at 36 weeks. For most women (96), there had been no prior suspicion of noncephalic presentation. ECV was attempted for 84 (46.9%) women and was successful in 12 (success rate: 14.3%). Overall, 19 of the 179 women delivered vaginally (10.6%), 110 delivered by elective cesarean section (ELCS) (61.5%) and 50 delivered by emergency cesarean section (EMCS) (27.9%). There were no women with undiagnosed breech presentation in labour in the entire cohort. On average, 40 scans were needed per detection of a previously undiagnosed breech presentation. The economic analysis indicated that, compared to current practice, universal late-pregnancy ultrasound would identify around 14,826 otherwise undiagnosed breech presentations across England annually. It would also reduce EMCS and vaginal breech deliveries by 0.7 and 1.0 percentage points, respectively: around 4,196 and 6,061 deliveries across England annually. Universal ultrasound would also prevent 7.89 neonatal mortalities annually. The strategy would be cost effective if foetal presentation could be assessed for £19.80 or less per woman. Limitations to this study included that foetal presentation was revealed to all women and that the health economic analysis may be altered by parity.

CONCLUSIONS

According to our estimates, universal late pregnancy ultrasound in nulliparous women (1) would virtually eliminate undiagnosed breech presentation, (2) would be expected to reduce foetal mortality in breech presentation, and (3) would be cost effective if foetal presentation could be assessed for less than £19.80 per woman.