Predictability of Macrosomic Birth based on Maternal Factors and Fetal Aneuploidy Screening Biochemical Markers in Hyperglycemic Mothers

Multivariable prediction models for fetal macrosomia and large for gestational age: A systematic review

BACKGROUND

The identification of large for gestational age (LGA) and macrosomic fetuses is essential for counselling and managing these pregnancies.

OBJECTIVES

To systematically review the literature for multivariable prediction models for LGA and macrosomia, assessing the performance, quality and applicability of the included model in clinical practice.

SEARCH STRATEGY

MEDLINE, EMBASE and Cochrane Library were searched until June 2022.

SELECTION CRITERIA

We included observational and experimental studies reporting the development and/or validation of any multivariable prediction model for fetal macrosomia and/or LGA. We excluded studies that used a single variable or did not evaluate model performance.

DATA COLLECTION AND ANALYSIS

Data were extracted using the Checklist for critical appraisal and data extraction for systematic reviews of prediction modelling studies checklist. The model performance measures discrimination, calibration and validation were extracted. The quality and completion of reporting within each study was assessed by its adherence to the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) checklist. The risk of bias and applicability were measured using PROBAST (Prediction model Risk Of Bias Assessment Tool).

MAIN RESULTS

A total of 8442 citations were identified, with 58 included in the analysis: 32/58 (55.2%) developed, 21/58 (36.2%) developed and internally validated and 2/58 (3.4%) developed and externally validated a model. Only three studies externally validated pre-existing models. Macrosomia and LGA were differentially defined by many studies. In total, 111 multivariable prediction models were developed using 112 different variables. Model discrimination was wide ranging area under the receiver operating characteristics curve (AUROC 0.56-0.96) and few studies reported calibration (11/58, 19.0%). Only 5/58 (8.6%) studies had a low risk of bias.

CONCLUSIONS

There are currently no multivariable prediction models for macrosomia/LGA that are ready for clinical implementation.

Obesity and oocyte quality: Significant implications for ART and Emerging mechanistic insights

The prevalence of obesity in adults worldwide, and specifically in women of reproductive age, is concerning given the risks to fertility posed by the increased risk of type 2 diabetes, metabolic syndrome and other non-communicable diseases. Obesity has a multi-systemic impact in female physiology that is characterized by the presence of oxidative stress, lipotoxicity, and the activation of pro-inflammatory pathways, inducing tissue-specific insulin resistance and ultimately conducive to abnormal ovarian function. A higher body mass is linked to Polycystic Ovary Syndrome, dysregulated menstrual cycles, anovulation, and longer time to pregnancy, even in ovulatory women. In the context of ART, compared to women of normal BMI, obese women have worse outcomes in every step of their journey, resulting in reduced success measured as live birth rate. Even after pregnancy is achieved, obese women have a higher chance of miscarriage, gestational diabetes, pregnancy complications, birth defects, and most worryingly, a higher risk of stillbirth and neonatal death. The potential for compounding effects of ART on pregnancy complications and infant morbidities in obese women has not been studied. There is still much debate in the field on whether these poorer outcomes are mainly driven by defects in oocyte quality, abnormal embryo development or an unaccommodating uterine environment, however the clinical evidence to date suggests a combination of all three are responsible. Animal models of maternal obesity shed light on the mechanisms underlaying the effects of obesity on the peri-conception environment, with recent findings pointing to lipotoxicity in the ovarian environment as a key driver of defects in oocytes that have not only reduced developmental competence but long-lasting effects in offspring health.