A new algorithm for improving fetal weight estimation from ultrasound data at term

The combination of symphysis-fundal height and abdominal circumference as a novel predictor of macrosomia in GDM and normal pregnancy

Background

Macrosomia is a major adverse pregnancy outcome of gestational diabetes mellitus (GDM). Although BMI, symphysis-fundal height (SFH) and abdominal circumference (AC) are associated with foetal weight, there are some limitations to their use, especially for the prediction of macrosomia. This study aimed to identify a novel predictive methodology to improve the prediction of high-risk macrosomia.

Methods

Clinical information was collected from 3730 patients. The association between the ISFHAC (index of the SFH algorithm multiplied by the square of AC) and foetal weight was determined and validated. A new index, the ISFHAC, was evaluated by area under the curve (AUC) analysis.

Results

A total of 1087 GDM and 657 normal singleton pregnancies were analysed. The ISFHAC was positively correlated with foetal weight in GDM pregnancies and normal pregnancies (NPs). The AUCs of the ISFHAC were 0.815 in the GDM group and 0.804 in the NP group, which were higher than those of BMI, SFH, AC and GA. The ISFHAC cut-off points were 41.7 and 37 in the GDM and NP groups, respectively. The sensitivity values for the prediction of macrosomia with high ISFHAC values were 75.9 and 81.3% in the GDM and NP groups, respectively, which were higher than those with BMI. Regarding the validation data, the sensitivity values for prediction with high ISFHAC values were 78.9% (559 GDM pregnancies) and 78.3% (1427 NPs).

Conclusions

The ISFHAC can be regarded as a new predictor of and risk factor for macrosomia in GDM pregnancy and NP.

A simple model to predict the complicated operative vaginal deliveries using vacuum or forceps

BACKGROUND

Complicated operative vaginal deliveries are associated with high neonatal morbidity and maternal trauma, especially if the procedure is unsuccessful and a cesarean delivery is needed. The decision to perform an operative vaginal delivery has traditionally been based on a subjective assessment by digital vaginal examination combined with the clinical expertise of the obstetrician. Currently there is no method for objectively quantifying the likelihood of successful delivery. Intrapartum ultrasound has been introduced in clinical practice to help predict the progression and final method of delivery.

OBJECTIVE

The aim of this study was to compare predictive models for identifying complicated operative vaginal deliveries (vacuum or forceps) based on intrapartum transperineal ultrasound in nulliparous women.

STUDY DESIGN

We performed a prospective cohort study in nulliparous women at term with singleton pregnancies and full dilatation who underwent intrapartum transperineal ultrasound evaluation prior to operative vaginal delivery. Managing obstetricians were blinded to the ultrasound data. Intrapartum transperineal ultrasound (angle of progression, progression distance, and midline angle) was performed immediately before instrument application, both at rest and concurrently with pushing. Intrapartum evaluation of fetal biometric parameters (estimated fetal weight, head circumference, and biparietal diameter) was also carried out. An operative vaginal delivery was classified as complicated when 1 or more of the following complications occurred: ≥3 tractions needed; third- to fourth-degree perineal tear; severe bleeding during episiotomy repair (decrease of ≥2.5 g/dL in the hemoglobin level); or significant traumatic neonatal lesion (subdural-intracerebral hemorrhage, epicranial subaponeurotic hemorrhage, skeletal injuries, injuries to spine and spinal cord, or peripheral and cranial nerve injuries). Six predictive models were evaluated (information available in Table 2).

RESULTS

We recruited 84 nulliparous patients, of whom 5 were excluded because of the difficulty of adequately evaluating the biparietal diameter and head circumference. A total of 79 nulliparous patients were studied (47 vacuum deliveries, 32 forceps deliveries) with 13 cases in the occiput-posterior position. We identified 31 cases of complicated operative vaginal deliveries (19 vacuum deliveries and 12 forceps deliveries). No differences were identified in obstetric, neonatal, or intrapartum characteristics between the 2 study groups (operative uncomplicated vaginal delivery vs operative complicated vaginal delivery), with the following exceptions: estimated fetal weight (3243 ± 425 g vs 3565 ± 330 g; P = .001), biparietal diameter (93.2 ± 2.1 vs 95.2 ± 2.3 mm; P = .001), head circumference (336 ± 12 vs 348 ± 6.4 mm; P = .001), sex (female 62.5% vs 29.0%; P = .010), newborn weight (3258 ± 472 g vs 3499 ± 383 g; P = .027), and number of tractions (median, interquartile range) (1 [1-2] vs 4 [3-5]; P < .0005). To predict complicated operative deliveries, all 6 of the studied models presented an area under the receiver-operating characteristics curve between 0.863 and 0.876 (95% confidence intervals, 0.775-0.950 and 0.790-0.963; P < .0005). The results of the study met the criteria of interpretability and parsimony (simplicity), allowing us to identify a binary logistic regression model based on the angle of progression and head circumference; this model has an area under the receiver-operating characteristics curve of 0.876 (95% confidence interval, 0.790-0.963; P < .0005) and a calibration slope B of 0.984 (95% confidence interval, 0.0.726-1.243; P < .0005).

CONCLUSION

The combination of the angle of progression and the head circumference can predict 87% of complicated operative vaginal deliveries and can be performed in the delivery room.

Predicting birth weight with conditionally linear transformation models

Low and high birth weight (BW) are important risk factors for neonatal morbidity and mortality. Gynecologists must therefore accurately predict BW before delivery. Most prediction formulas for BW are based on prenatal ultrasound measurements carried out within one week prior to birth. Although successfully used in clinical practice, these formulas focus on point predictions of BW but do not systematically quantify uncertainty of the predictions, i.e. they result in estimates of the conditional mean of BW but do not deliver prediction intervals. To overcome this problem, we introduce conditionally linear transformation models (CLTMs) to predict BW. Instead of focusing only on the conditional mean, CLTMs model the whole conditional distribution function of BW given prenatal ultrasound parameters. Consequently, the CLTM approach delivers both point predictions of BW and fetus-specific prediction intervals. Prediction intervals constitute an easy-to-interpret measure of prediction accuracy and allow identification of fetuses subject to high prediction uncertainty. Using a data set of 8712 deliveries at the Perinatal Centre at the University Clinic Erlangen (Germany), we analyzed variants of CLTMs and compared them to standard linear regression estimation techniques used in the past and to quantile regression approaches. The best-performing CLTM variant was competitive with quantile regression and linear regression approaches in terms of conditional coverage and average length of the prediction intervals. We propose that CLTMs be used because they are able to account for possible heteroscedasticity, kurtosis, and skewness of the distribution of BWs.

Accuracy of sonographic prediction of birth weight

Many clinicians use ultrasound estimates of fetal weight to assess fetal growth. This study assessed the accuracy of the Hadlock IV equation, the equation used at the Royal Hospital for Women, Randwick, NSW, in estimating birth weight. The accuracy of the Hadlock IV equation was assessed based on systematic and random error as well as absolute error. 709 women who underwent ultrasound examination within 8 weeks of delivery between January 2009-May 2011 were included. 305 women underwent ultrasound less than 2 weeks before delivery. The systematic, random and absolute errors of the Hadlock IV equation were -0.47, 27.45 and 8.52%, respectively. This study demonstrates that clinicians may rely on ultrasound estimates of fetal weight performed by well-trained staff in a tertiary institution within 2 weeks of delivery. The accuracy diminishes as the interval between testing and delivery increases. Absolute errors tended to increase with increasing birth weight for all ultrasound-delivery intervals.