Prediction of small-for-gestational age by fetal growth rate according to gestational age

Prognostic prediction models for adverse birth outcomes: A systematic review

Background

Despite progress in reducing maternal and child mortality worldwide, adverse birth outcomes such as preterm birth, low birth weight (LBW), small for gestational age (SGA), and stillbirth continue to be a major global health challenge. Developing a prediction model for adverse birth outcomes allows for early risk detection and prevention strategies. In this systematic review, we aimed to assess the performance of existing prediction models for adverse birth outcomes and provide a comprehensive summary of their findings.

Methods

We used the Population, Index prediction model, Comparator, Outcome, Timing, and Setting (PICOTS) approach to retrieve published studies from PubMed/MEDLINE, Scopus, CINAHL, Web of Science, African Journals Online, EMBASE, and Cochrane Library. We used WorldCat, Google, and Google Scholar to find the grey literature. We retrieved data before 1 March 2022. Data were extracted using CHecklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies. We assessed the risk of bias with the Prediction Model Risk of Bias Assessment tool. We descriptively reported the results in tables and graphs.

Results

We included 115 prediction models with the following outcomes: composite adverse birth outcomes (n = 6), LBW (n = 17), SGA (n = 23), preterm birth (n = 71), and stillbirth (n = 9). The sample sizes ranged from composite adverse birth outcomes (n = 32-549), LBW (n = 97-27 233), SGA (n = 41-116 070), preterm birth (n = 31-15 883 784), and stillbirth (n = 180-76 629). Only nine studies were conducted on low- and middle-income countries. 10 studies were externally validated. Risk of bias varied across studies, in which high risk of bias was reported on prediction models for SGA (26.1%), stillbirth (77.8%), preterm birth (31%), LBW (23.5%), and composite adverse birth outcome (33.3%). The area under the receiver operating characteristics curve (AUROC) was the most used metric to describe model performance. The AUROC ranged from 0.51 to 0.83 in studies that reported predictive performance for preterm birth. The AUROC for predicting SGA, LBW, and stillbirth varied from 0.54 to 0.81, 0.60 to 0.84, and 0.65 to 0.72, respectively. Maternal clinical features were the most utilised prognostic markers for preterm and LBW prediction, while uterine artery pulsatility index was used for stillbirth and SGA prediction.

Conclusions

A varied prognostic factors and heterogeneity between studies were found to predict adverse birth outcomes. Prediction models using consistent prognostic factors, external validation, and adaptation of future risk prediction models for adverse birth outcomes was recommended at different settings.

Registration

PROSPERO CRD42021281725.

Prediction of small-for-gestational-age neonates at 33-39 weeks' gestation in China: logistic regression modeling of the contributions of second- and third-trimester ultrasound data and maternal factors

Objectives

A screening model for prediction of small-for-gestational-age (SGA) neonates (SGAp) was established by logistic regression using ultrasound data and maternal factors (MF). We aimed to evaluate the ability of SGAp as well as abdominal circumference (AC) and estimated fetal weight (EFW) measurements to predict SGA neonates at 33–39 weeks’ gestation.

Methods

This retrospective study evaluated 5298 singleton pregnancies that had involved three ultrasound examinations at 21⁺⁰–27⁺⁶, 28⁺⁰–32⁺⁶, and 33⁺⁰–39⁺⁶ weeks. All ultrasound data were transformed to MoM values (multiple of the median). Multivariate logistic regression was used to analyze the correlation between SGA status and various variables (ultrasound data and MF) during pregnancy to build the SGAp model. EFW was calculated according to the Hadlock formula at 33–39 weeks of gestation. The predictive performance of SGAp, AC MoM value at 33⁺⁰–39⁺⁶ weeks (AC-M), EFW MoM value (EFW-M), EFW-M plus MF, AC value at 33⁺⁰–39⁺⁶ weeks (AC), AC growth velocity, EFW, and EFW plus MF was evaluated using ROC curves. The detection rate (DR) of SGA neonate with SGAp, AC-M, EFW-M, and EFW-M plus MF at false positive rate (FPR) of 5% and 10%, and the FPR at DR of 85%, 90%, and 95% were observed.

Results

The AUCs of SGAp, AC-M, EFW-M, EFW-M plus MF, AC, AC growth velocity, EFW, and EFW plus MF for SGA neonates screening were 0.933 (95%CI: 0.916–0.950), 0.906 (95%CI: 0.887–0.925), 0.920 (95%CI: 0.903–0.936), 0.925 (95%CI: 0.909–0.941), 0.818 (95%CI: 0.791–0.845), 0.786 (95%CI: 0.752–0.821), 0.810 (95%CI: 0.782–0.838), and 0.834 (95%CI: 0.807–0.860), respectively. The screening efficiency of SGAp, AC-M, EFW-M, and EFW-M plus MF are significantly higher than AC, AC growth velocity, EFW, and EFW plus MF. The DR of SGAp, AC-M, EFW-M, and EFW-M plus MF for SGA neonates were 80.4%, 69.6%, 73.8% and 74.3% at 10% FPR. The AUCs of SGAp, AC-M, EFW-M, and EFW-M plus MF 0.950 (95%CI: 0.932–0.967), 0.929 (95%CI: 0.909–0.948), 0.938 (95%CI: 0.921–0.956) and 0.941 (95%CI: 0.924–0.957), respectively for screening SGA neonates delivered within 2 weeks after the assessment. The DR for these births increased to 85.8%, 75.8%, 80.0%, and 82.5%, respectively.

Conclusion

The rational use of ultrasound data can significantly improve the prediction of SGA statuses.

The effect of snakehead fish (Channa striata) cookies supplementation on fetal growth and birth outcomes: A randomized clinical trial

BACKGROUND: An estimated 15–20% of all births worldwide are low birth weight (LBW). In Indonesia, the LBW incidence reached more than 10% in 2013. Improved maternal nutrition is needed by providing high-calorie-protein supplementation for pregnant women to prevent intrauterine growth retardation and LBW. OBJECTIVES: To observe the effect of snakehead fish (Channa striata) cookies supplementation during pregnancy on fetal growth and birth outcomes. METHODS: A total of 50 pregnant women were included in this randomized controlled trial study and were randomly allocated into two groups: treatment and controls. Subjects in the treatment group received supplementation of snakehead fish cookies during pregnancy until giving birth as much as 75 g per day, while subjects in the control group received standard cookies. The snakehead fish cookies underwent a formulation process and were tested for nutrient content and microbial contamination to ensure safety before being given to the subjects. Fetal growth was monitored monthly using 2-dimensional ultrasonography. RESULTS: The average intake of cookies did not differ between the two groups (Control 69.6 (16.8)% vs Snakehead fish 64.6 (15.3)%, p = 0.278). There were no significant differences in fetal estimated fetal weight, biparietal diameter, abdominal circumference, femur length, birth weight, and birth length between the treatment and control groups (p >  0.05). However, the fetal growth measurements on the subjects who consumed snakehead fish cookies were practically higher than those who ate standard cookies. CONCLUSION: The snakehead fish cookies did improve the fetal growth measurements but the results were not significantly different when compared to standard cookies.

Estimation of multiple ordered ROC curves using placement values

In many diagnostic accuracy studies, a priori orders may be available on multiple receiver operating characteristic curves. For example, being closer to delivery, fetal ultrasound measures in the third trimester should be no less accurate than those in the second trimester in predicting small-for-gestational-age births. Such an a priori order should be incorporated in estimating receiver operating characteristic curves and associated summary accuracy statistics, as it can potentially improve statistical efficiency of these estimates. Early work in the literature has mainly taken an indirect approach to this task and has induced the desired a priori order through modeling test score distributions. We instead propose a new strategy that incorporates the order directly through the modeling of receiver operating characteristic curves. We achieve this by exploiting the link between placement value (the relative position of a diseased test score in the healthy score distribution), the cumulative distribution function of placement value, and receiver operating characteristic curve, and by building stochastically ordered random variables through mixture distributions. We take a Bayesian semiparametric approach in using Dirichlet process mixture models so that the placement values can be flexibly modeled. We conduct extensive simulation studies to examine the performance of the proposed methodology and apply the new framework to data from obstetrics and women's health studies.

Alterations of brain metrics in fetuses of women with polycystic ovary syndrome : a retrospective study based on fetal magnetic resonance imaging

Background

Maternal polycystic ovary syndrome (PCOS) has potential detrimental effects on the neurodevelopment of offspring. This study aimed to evaluate the brain metrics in fetuses of women with PCOS based on fetal magnetic resonance imaging (MRI).

Methods

This retrospective study included 60 pregnant women with PCOS (PCOS group) and 120 pregnant non-PCOS women (control group). Fetal MRI was performed followed an ultrasound and for numerous clinical indications including known or suspected fetal pathology, history of fetal abnormality in previous pregnancy or in a family member. Fetal brain biometry and apparent diffusion coefficient (ADC) value were analysed.

Results

After adjusting for potential confounders, fetuses in the PCOS group showed the following characteristics compared to fetuses in the control group: (1) smaller cerebral fronto-occipital diameter (FOD), vermian height (VH) and anteroposterior diameter of the pons (APDP) (evident before 32 weeks; P = 0.042, P = 0.002 and P = 0.016, respectively); (2) larger left and right biparietal index (evident before 32 weeks; P = 0.048 and P = 0.025, respectively); (3) smaller left lateral ventricle (LV) (evident after 32 weeks; P = 0.005); (4) larger anteroposterior diameter of the vermis (APDV) and hippocampal infolding angle (HIA) (evident after 32 weeks; P = 0.003 and P < 0.001, respectively); (5) higher ADC value in frontal white matter (FWM) and in basal ganglia (BG) (evident before and after 32 weeks; all P < 0.05).

Conclusions

There exist a different pattern of brain metrics in PCOS offspring in utero.

Fetal growth, fetal development, and placental features in women with polycystic ovary syndrome: analysis based on fetal and placental magnetic resonance imaging

OBJECTIVE

Polycystic ovary syndrome (PCOS), a common endocrine-metabolic dysfunction in reproductive-aged women, may be involved in compromised pregnancy and offspring outcomes. This study aimed to investigate whether maternal PCOS affects fetal growth, fetal development, and placental features.

METHODS

This retrospective case-control study included 60 pregnant women with PCOS (PCOS group) and 120 healthy pregnant women without PCOS (control group). Fetal magnetic resonance imaging (MRI) was performed followed by an ultrasound examination and indications for imaging, including known or suspected fetal pathology, history of fetal abnormality in previous pregnancy or in a family member, and concern for placenta accreta. Fetal MRI images were analyzed for head circumference (HC), abdomen circumference (AC), lung-to-liver signal intensity ratio (LLSIR, a prenatal marker of fetal lung maturity), lengths of liver and kidney diameters in fetuses, and placental relative signal intensity on T2-weighted single-shot fast spin echo (SSFSE) imaging (rSISSFSE), and placental relative apparent diffusion coefficient value (rADC). Data on height and weight of offspring were collected through telephone follow-up.

RESULTS

Compared to the control group, the PCOS group showed the following characteristics: (1) smaller biparietal diameter and femur length in fetuses (P=0.026 and P=0.005, respectively), (2) smaller HC in fetuses (evident after 32 weeks; P=0.044), (3) lower LLSIR and smaller dorsoventral length of liver in fetuses (evident before 32 weeks; P=0.005 and P=0.019, respectively), and (4) smaller placental thickness (evident before 32 weeks; P=0.017). No significant differences in placental rSISSFSE or rADC were observed between the groups (all P>0.05). No significant differences in height and weight of offspring during childhood existed between the groups (all P>0.05).

CONCLUSIONS

There exist alterations of fetal growth, fetal development, and placental features from women with PCOS.