Accelerated fetal growth velocity across the third trimester is associated with increased shoulder dystocia risk among fetuses who are not large-for-gestational-age: A prospective observational cohort study

Shoulder dystocia by severity in families: A nationwide population study

INTRODUCTION

Previous studies have established a history of shoulder dystocia as an important risk factor for shoulder dystocia, but studies on shoulder dystocia by severity are scarce. It is unknown if shoulder dystocia tends to be passed on between generations. We aimed to assess the recurrence risk of shoulder dystocia by severity in the same woman and between generations on both the maternal and paternal side. We also assessed the likelihood of a second delivery and planned cesarean section after shoulder dystocia.

MATERIAL AND METHODS

This was a population-based cohort study, using data from the Medical Birth Registry of Norway. To study recurrence in the same mother, we identified 1 091 067 pairs of first and second, second and third, and third and fourth births in the same mother. To study intergenerational recurrence, we identified an individual both as a newborn and as a mother or father in 824 323 mother-offspring pairs and 614 663 father-offspring pairs. We used Bayesian log-binomial multilevel regression to calculate relative risks (RR) with 95% credible intervals.

RESULTS

In subsequent deliveries in the same woman the unadjusted RR of recurrence was 7.05 (95% credible interval 6.39-7.79) and 2.99 (2.71-3.31) after adjusting for possible confounders, including current birthweight. The RRs were higher with severe shoulder dystocia as exposure or outcome. With severe shoulder dystocia as both exposure and outcome, unadjusted and adjusted RR was 20.42 (14.25-29.26) and 6.29 (4.41-8.99), respectively. Women with severe and mild shoulder dystocia and those without had subsequent delivery rates of 71.1, 68.9 and 69.0%, respectively. However, the rates of planned cesarean section in subsequent deliveries for those without shoulder dystocia, mild and severe were 1.3, 5.2 and 16.0%, respectively. On the maternal side the unadjusted inter-generational RR of recurrence was 2.82 (2.25-3.54) and 1.41 (1.05-1.90) on the paternal side. Corresponding adjusted RRs were 1.90 (1.51-2.40) and 1.19 (0.88-1.61), respectively.

CONCLUSIONS

We found a strong recurrence risk of shoulder dystocia, especially severe, in subsequent deliveries in the same woman. The inter-generational recurrence risk was higher on the maternal than paternal side. Women with a history of shoulder dystocia had more often planned cesarean section.

Analytical Comparison of Risk Prediction Models for the Onset of Macrosomia Based on Three Statistical Methods

Background and Purpose. Fetal overgrowth can pose a serious threat to the safety of a mother and child. Early identification of high-risk pregnant women and timely pregnancy intervention and guidance are of great value in preventing the development of giant babies and improving adverse maternal and infant outcomes. The current clinical methods for predicting macrosomia mainly rely on obstetric examination and imaging, but their accuracy is controversial. And there is no accepted method for accurately predicting macrosomia. We investigated the risk factors influencing the occurrence of macrosomia and established a prediction model for the occurrence of macrosomia to provide a reference basis for interventions to prevent macrosomia. Method. A retrospective selection of 93 women who were hospitalized in our hospital from March 2019 to May 2022 with a singleton pregnancy and delivered at term with macrosomia were the study group. And 356 women who delivered a normal size baby during the same period were the control group. The variables that were associated with the onset of macrosomia were screened from maternal medical records. Logistic regression models, random forest, and CART decision tree models were developed using the screened variables as input variables and whether they were macrosomia as outcome variables, respectively. The performance of the three models was evaluated by accuracy, precision, recall, F1 score, and receiver operating characteristic curve (ROC). Result. The risk prediction models for the onset of macrosomia, logistic regression model, random forest model, and decision tree, were successfully developed, with accuracies of 0.904, 1.000, and 0.901 in the training set and 0.926, 0.582, and 0.852 in the validation set, respectively. The AUC in the training set were 0.898, 1.000, and 0.789, and in the validation set were 0.906, 0.913, and 0.731, respectively. In general, the logistic regression model has the highest diagnostic efficiency, followed by the random forest model. Conclusion. Logistic regression models have high application value in the assessment of predicting the risk of macrosomia, and it is suggested that the advantages of logistic regression models and random forest models should be combined in future studies and applications to make them work better in the prediction of the risk of macrosomia.

Late pregnancy ultrasound parameters identifying fetuses at risk of adverse perinatal outcomes: a protocol for a systematic review of systematic reviews

INTRODUCTION

Stillbirths and neonatal deaths are leading contributors to the global burden of disease and pregnancy ultrasound has the potential to help decrease this burden. In the absence of high-Grading of Recommendations Assessment, Development and Evaluation (GRADE) evidence on universal obstetric ultrasound screening at or close to term, many different screening strategies have been proposed. Systematic reviews have rapidly increased over the past decade owing to the diverse nature of ultrasound parameters and the wide range of possible adverse perinatal outcomes. This systematic review will summarise the evidence on key ultrasound parameters in the published literature to help develop an obstetric ultrasound protocol that identifies pregnancies at risk of adverse perinatal outcomes at or close to term.

METHODS

This study will follow the recent Cochrane guidelines for a systematic review of systematic reviews. A comprehensive literature search will be conducted using Embase (OvidSP), Medline (OvidSP), CDSR, CINAHL (EBSCOhost) and Scopus. Systematic reviews evaluating at least one ultrasound parameter in late pregnancy to detect pregnancies at risk of adverse perinatal outcomes will be included. Two independent reviewers will screen, assess the quality including the risk of bias using the ROBIS tool, and extract data from eligible systematic reviews that meet the study inclusion criteria. Overlapping data will be assessed and managed with decision rules, and study evidence including the GRADE assessment of the certainty of results will be presented as a narrative synthesis as described in the Cochrane guidelines for an overview of reviews.

ETHICS AND DISSEMINATION

This research uses publicly available published data; thus, an ethics committee review is not required. The findings will be published in a peer-reviewed journal.

PROSPERO REGISTRATION NUMBER

CRD42021266108.