Stillbirth: fetal disorders

Proposing a machine-learning based method to predict stillbirth before and during delivery and ranking the features: nationwide retrospective cross-sectional study

Background

Stillbirth is defined as fetal loss in pregnancy beyond 28 weeks by WHO. In this study, a machine-learning based method is proposed to predict stillbirth from livebirth and discriminate stillbirth before and during delivery and rank the features.

Method

A two-step stack ensemble classifier is proposed for classifying the instances into stillbirth and livebirth at the first step and then, classifying stillbirth before delivery from stillbirth during the labor at the second step. The proposed SE has two consecutive layers including the same classifiers. The base classifiers in each layer are decision tree, Gradient boosting classifier, logistics regression, random forest and support vector machines which are trained independently and aggregated based on Vote boosting method. Moreover, a new feature ranking method is proposed in this study based on mean decrease accuracy, Gini Index and model coefficients to find high-ranked features.

Results

IMAN registry dataset is used in this study considering all births at or beyond 28th gestational week from 2016/04/01 to 2017/01/01 including 1,415,623 live birth and 5502 stillbirth cases. A combination of maternal demographic features, clinical history, fetal properties, delivery descriptors, environmental features, healthcare service provider descriptors and socio-demographic features are considered. The experimental results show that our proposed SE outperforms the compared classifiers with the average accuracy of 90%, sensitivity of 91%, specificity of 88%. The discrimination of the proposed SE is assessed and the average AUC of ±95%, CI of 90.51% ±1.08 and 90% ±1.12 is obtained on training dataset for model development and test dataset for external validation, respectively. The proposed SE is calibrated using isotopic nonparametric calibration method with the score of 0.07. The process is repeated 10,000 times and AUC of SE classifiers using random different training datasets as null distribution. The obtained p-value to assess the specificity of the proposed SE is 0.0126 which shows the significance of the proposed SE.

Conclusions

Gestational age and fetal height are two most important features for discriminating livebirth from stillbirth. Moreover, hospital, province, delivery main cause, perinatal abnormality, miscarriage number and maternal age are the most important features for classifying stillbirth before and during delivery.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12884-021-03658-z.

3137 fetuses in 33 years: What we have learned from the Wisconsin stillbirth service program

The Wisconsin Stillbirth Service Program (WiSSP) provided expert review by a dysmorphologist for community-acquired data on 3137 fetal deaths between 1983 and 2017. Intrinsic fetal causes were consistently identified in about 25% while placental and maternal causes were recognized with increasing frequency as attention was shifted from a primarily fetal to a multifocal approach. Identification of causes increased from 40% to 78% and in about half of cases results of the review altered recurrence risk and/or future pregnancy management. Banked data from WiSSP formed the basis of 24 publications, more than half of which have a genetic counselor and/or summer premedical student intern as an author. The earlier publications emphasized validation of the concept of community-based evaluation with central review, the utility of various parts of the WiSSP protocol, the similarity of second-trimester miscarriages <20 weeks to later stillbirths with respect to causes identified and recurrence risks, and the potential for results of etiologic evaluation to influence future prenatal care. The most important recurrent theme, however, was the interaction of intrinsic fetal, placental, and maternal factors in contributing to fetal demise. This implies that, at least in developed nations with available obstetric care, reduction in stillbirth will require careful attention to the myriad of factors contributing to fetal, placental, and maternal well-being.

"The First Thousand Days" Define a Fetal/Neonatal Neurology Program

Gene-environment interactions begin at conception to influence maternal/placental/fetal triads, neonates, and children with short- and long-term effects on brain development. Life-long developmental neuroplasticity more likely results during critical/sensitive periods of brain maturation over these first 1,000 days. A fetal/neonatal program (FNNP) applying this perspective better identifies trimester-specific mechanisms affecting the maternal/placental/fetal (MPF) triad, expressed as brain malformations and destructive lesions. Maladaptive MPF triad interactions impair progenitor neuronal/glial populations within transient embryonic/fetal brain structures by processes such as maternal immune activation. Destructive fetal brain lesions later in pregnancy result from ischemic placental syndromes associated with the great obstetrical syndromes. Trimester-specific MPF triad diseases may negatively impact labor and delivery outcomes. Neonatal neurocritical care addresses the symptomatic minority who express the great neonatal neurological syndromes: encephalopathy, seizures, stroke, and encephalopathy of prematurity. The asymptomatic majority present with neurologic disorders before 2 years of age without prior detection. The developmental principle of ontogenetic adaptation helps guide the diagnostic process during the first 1,000 days to identify more phenotypes using systems-biology analyses. This strategy will foster innovative interdisciplinary diagnostic/therapeutic pathways, educational curricula, and research agenda among multiple FNNP. Effective early-life diagnostic/therapeutic programs will help reduce neurologic disease burden across the lifespan and successive generations.

Pathology of the stillborn infant for the general pathologist: part 1

As the information obtained from previable fetal and stillbirth autopsies is used not only to explain the loss to the parents, but for future pregnancy planning, general pathologists need to be comfortable in dealing with these autopsies. The importance of an adequate fetal examination has been emphasized in a recent policy on the subject by the American Board of Pathology http://www.abpath.org/FetalAutopsyPolicy.pdf. This review paper covers the approach to the fetal and stillbirth autopsy. This first article covers the approach to the nonanomalous and anomalous autopsy. Hydrops fetalis will be covered in the second part of this series to be published subsequently.

Routine perinatal and paediatric post-mortem radiography: detection rates and implications for practice

BACKGROUND

Routine perinatal and paediatric post-mortem plain radiography allows for the diagnosis and assessment of skeletal dysplasias, fractures and other bony abnormalities.

OBJECTIVE

The aim of this study was to review the diagnostic yield of this practice.

MATERIALS AND METHODS

We identified 1,027 cases performed in a single institution over a 2½-year period, including babygrams (whole-body examinations) and full skeletal surveys. Images were reported prior to autopsy in all cases. Radiology findings were cross-referenced with the autopsy findings using an autopsy database. We scored each case from 0 to 4 according to the level of diagnostic usefulness.

RESULTS

The overall abnormality rate was 126/1,027 (12.3%). There was a significantly higher rate of abnormality when a skeletal survey was performed (18%) rather than a babygram (10%; P < 0.01); 90% (665/739) of babygrams were normal. Of the 74 abnormal babygrams, we found 33 incidental non-contributory cases, 19 contributory, 20 diagnostic, and 2 false-positive cases. There were only 2 cases out of 739 (0.27%) in whom routine post-mortem imaging identified potentially significant abnormalities that would not have been detected if only selected imaging had been performed. A policy of performing selected, rather than routine, foetal post-mortem radiography could result in a significant cost saving.

CONCLUSION

Routine post-mortem paediatric radiography in foetuses and neonates is neither diagnostically useful nor cost-effective. A more evidence-based, selective protocol should yield significant cost savings.