Maternal and neonatal complications of fetal macrosomia: systematic review and meta-analysis

The impact of maternal prepregnancy impaired fasting glucose on preterm birth and large for gestational age: a large population-based cohort study

BACKGROUND

The impact of maternal prepregnancy impaired fasting glucose on preterm birth and large for gestational age has been poorly understood.

OBJECTIVES

We aimed to estimate the impact of prepregnancy impaired fasting glucose defined by the World Health Organization cut point on the risk of preterm birth and large for gestational age and to investigate whether the World Health Organization cut point of impaired fasting glucose was appropriate for identifying women at risk of preterm birth and large for gestational age among the Chinese population.

STUDY DESIGN

This was a retrospective cohort study of women from the National Free Preconception Health Examination Project with singleton birth from 121 counties/districts in 21 cities of Guangdong Province, China, from Jan. 1, 2013, to Dec. 31, 2017. Women were included if their prepregnancy fasting glucose was less than 7.0 mmol/L. The primary outcomes were preterm birth (gestational age <37 weeks), early preterm birth (gestational age <34 weeks), large for gestational age (birthweight by gestational age >90th percentile based on the international standards in the International Fetal and Newborn Growth Consortium for the 21st Century study), and severe large for gestational age (birthweight by gestational age >97th percentile). We calculated the adjusted risk ratio for impaired fasting glucose and a 1 standard deviation increase in fasting glucose.

RESULTS

We included 640,469 women. Of these, 31,006 (4.84%) met the World Health Organization cut point for impaired fasting glucose, 32,640 (5.10%) had preterm birth and 7201 (1.12%) had early preterm birth, 45,532 (7.11%) had large for gestational age birth, and 16,231 (2.53%) had severe large for gestational age birth. Compared with women with normoglycaemia, women with prepregnancy impaired fasting glucose had a 7.0% higher risk of preterm birth (adjusted risk ratio, 1.07, 95% confidence interval, 1.02-1.12), 10.0% had a higher risk of large for gestational age (adjusted risk ratio, 1.10, 95% confidence interval, 1.06-1.14), and 17.0% had a higher risk of severe large for gestational age (adjusted risk ratio, 1.17, 95% confidence interval, 1.10-1.26). No significant association of prepregnancy impaired fasting glucose with early preterm birth was found. The association of prepregnancy impaired fasting glucose with preterm birth and large for gestational age were similar in subgroups of women with various baseline characteristics. Adjusted risk ratio for preterm birth per standard deviation fasting glucose (0.7 mmol/L) was 0.99 (95% confidence interval, 0.98-1.00), for early preterm birth an adjusted risk ratio of 0.99 (confidence interval, 0.97-1.02), for large for gestational age an adjusted risk ratio of 1.04 (confidence interval, 1.03-1.05), and for severe large for gestational age an adjusted risk ratio of 1.03 (confidence interval, 1.01-1.04).

CONCLUSION

Our data suggest that maternal prepregnancy impaired fasting glucose increases the risk of preterm birth, large for gestational age, and severe large for gestational age. Data also suggest that the World Health Organization cut point of impaired fasting glucose is too restrictive, and lower levels of fasting glucose also increase the risk of large for gestational age and severe for severe gestational age in the Chinese population. Further investigation is warranted to determine whether and how counseling and interventions for women with prepregnancy impaired fasting glucose could reduce the risk of preterm birth and large for gestational age.

Impact of biometric measurement error on identification of small- and large-for-gestational-age fetuses

OBJECTIVES

First, to obtain measurement-error models for biometric measurements of fetal abdominal circumference (AC), head circumference (HC) and femur length (FL), and, second, to examine the impact of biometric measurement error on sonographic estimated fetal weight (EFW) and its effect on the prediction of small- (SGA) and large- (LGA) for-gestational-age fetuses with EFW < 10^th and > 90^th percentile, respectively.

METHODS

Measurement error standard deviations for fetal AC, HC and FL were obtained from a previous large study on fetal biometry utilizing a standardized measurement protocol and both qualitative and quantitative quality-control monitoring. Typical combinations of AC, HC and FL that gave EFW on the 10^th and 90^th percentiles were determined. A Monte-Carlo simulation study was carried out to examine the effect of measurement error on the classification of fetuses as having EFW above or below the 10^th and 90^th percentiles.

RESULTS

Errors were assumed to follow a Gaussian distribution with a mean of 0 mm and SDs, obtained from a previous well-conducted study, of 6.93 mm for AC, 5.15 mm for HC and 1.38 mm for FL. Assuming errors according to such distributions, when the 10^th and 90^th percentiles are used to screen for SGA and LGA fetuses, respectively, the detection rates would be 78.0% at false-positive rates of 4.7%. If the cut-offs were relaxed to the 30^th and 70^th percentiles, the detection rates would increase to 98.2%, but at false-positive rates of 24.2%. Assuming half of the spread in the error distribution, using the 10^th and 90^th percentiles to screen for SGA and LGA fetuses, respectively, the detection rates would be 86.6% at false-positive rates of 2.3%. If the cut-offs were relaxed to the 15^th and 85^th percentiles, respectively, the detection rates would increase to 97.0% and the false-positive rates would increase to 6.3%.

CONCLUSIONS

Measurement error in fetal biometry causes substantial error in EFW, resulting in misclassification of SGA and LGA fetuses. The extent to which improvement can be achieved through effective quality assurance remains to be seen but, as a first step, it is important for practitioners to understand how biometric measurement error impacts the prediction of SGA and LGA fetuses. © 2019 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

The Alteration of Carnitine Metabolism in Second Trimester in GDM and a Nomogram for Predicting Macrosomia

OBJECTIVE

The metabolism of three major nutrients (sugar, lipid, and protein) will change during pregnancy, especially in the second trimester. The present study is aimed at evaluating carnitine alteration in fatty acid metabolism in the second trimester of pregnancy and the correlation between carnitine and GDM.

METHODS

450 pregnant women were recruited in the present prospective study. Metabolic profiling of 31 carnitines was detected by LC-MS/MS in these women. Correlation between carnitine metabolism and maternal and neonatal complication with GDM was analyzed.

RESULTS

We found the levels of 7 carnitines increased in age > 35, BMI ≥ 30, weight gain > 20 kg, and ART pregnant groups, but the level of free carnitine (C0) decreased. Nine carnitines were specific metabolites of GDM. Prepregnancy BMI, weight gain, and carnitines (C0, C3, and C16) were independent risk factors associated with GDM and related macrosomia. C0 was negatively correlated with FBG, LDL, TG, and TC. A nomogram was developed for predicting macrosomia in GDM based on carnitine-related metabolic variables.

CONCLUSION

The carnitine metabolism in the second trimester is abnormal in GDM women. The dysfunction of carnitine metabolism is closely related to the abnormality of blood lipid and glucose in GDM. Carnitine metabolism abnormality could predict macrosomia complicated with GDM.

Excessive Maternal Weight and Diabetes Are Risk Factors for Macrosomia: A Cross-Sectional Study of 42,663 Pregnancies in Uruguay

OBJECTIVE

To evaluate the risk of macrosomia in newborns from women with gestational diabetes, pregestational diabetes, overweight, and obesity in Uruguay in 2012, as well as its association with prolonged pregnancy, maternal age, multiparity, and excessive gestational weight gain (EGWG).

METHODS

We performed a cross-sectional study of 42,663 pregnant women. The risk of macrosomia was studied using logistic regression.

RESULTS

Mean maternal age was 26.7 ± 6.8 years. Pregestational overweight and obesity was present in 20.9% and 10.7% of women, respectively. There were 28.1% and 19.8% of women overweight and obese at the end of the pregnancy, respectively. Furthermore, 0.5% had pregestational diabetes and 8.5% were multiparous. Twenty two percent developed gestational diabetes and 44.9% had EGWG. The prevalence of macrosomia was 7.9%, significantly more prevalent in males (10.0% vs. 5.5%, p<0.005). Univariate analysis showed that obesity and overweight pre-pregnancy, obesity and overweight at the end of pregnancy, EGWG, pregestational diabetes, gestational diabetes, multiparity, prolonged pregnancy, and male newborn were strongly associated with macrosomia (p<0.0001). Maternal age >35 years did not increase the risk of macrosomia. After multiple logistic regression macrosomia was more likely in pre-gestational obese women (OR 1.24; CI 1.07-1.44), overweight women at the end of pregnancy (OR 1.66; CI 1.46-1.87), obese women at the end of pregnancy (OR 2.21; CI 1.90-2.58), women with EGWG (OR 1.78; CI 1.59-1.98), pregestational diabetes (OR 1.75; CI 1.15-2.69), gestational diabetes (OR 1.39; CI 1.25-1.53), prolonged pregnancy (OR 2.67; CI 2.28-3.12), multiparity (OR 1.24; CI 1.04-1.48), and male newborn (OR 1.89; CI 1.72-2.08).

CONCLUSION

Maternal overweight, obesity, EGWG, and gestational diabetes are prevalent in Uruguay, increasing the risk of macrosomia. Efforts to implement strategies to decrease the prevalence of overweight and obesity among women of reproductive age are essential to improve maternal and neonatal outcomes.

Development of birth weight for gestational age charts and comparison with currently used charts: defining growth in the Polish population

OBJECTIVES

This study aimed to obtain the reference curves of birth weight for gestational age percentiles for the Polish population and to compare them to published charts in terms of detected proportions of small for gestational age (SGA) and large for gestational age (LGA).

METHODS

The reference curves of birth weight from 24 to 42 weeks of gestation were computed based on 39,092 singleton deliveries. The nomograms included the 3rd to the 97th percentiles and standard deviations. The percentiles were calculated for female and male newborns. The theoretical and true proportions of percentiles for the studied population were estimated based on six growth charts (Fenton, Intergrowth Project, global reference chart, Yudkin, Dubiel, and the World Health Organization chart).

RESULTS

The 50th percentile male and female newborns at 40 weeks weighed 3645.8 and 3486.7 g, respectively. The difference was 159.1 g. The ranges between the 3rd and 97th percentile at 40 weeks were 1481.5 g for males and 1423.5 for females. A total of 9.8% SGA and 10.27% LGA were defined, higher than that identified using the Fenton chart and even higher than that identified using the Intergrowth Project.

CONCLUSION

Population growth charts identify more newborns with abnormal growth (both LGA and SGA). The similarity between charts in LGA above the 95th percentile is observed. The discrepancies in SGA are significantly greater, specifically in preterm births than in term births. Similar coverage is found in term pregnancies, regardless of birth weight for gestational age or intrauterine charts. The feasibility of a Polish population growth chart needs to be validated for predicting adverse perinatal outcomes.

Prediction of large-for-gestational-age neonate by routine third-trimester ultrasound

OBJECTIVES

First, to evaluate and compare the performance of routine ultrasonographic estimated fetal weight (EFW) and fetal abdominal circumference (AC) at 31 + 0 to 33 + 6 and 35 + 0 to 36 + 6 weeks' gestation in the prediction of a large-for-gestational-age (LGA) neonate born at ≥ 37 weeks' gestation. Second, to assess the additive value of fetal growth velocity between 32 and 36 weeks' gestation to the performance of EFW at 35 + 0 to 36 + 6 weeks' gestation for prediction of a LGA neonate. Third, to define the predictive performance for a LGA neonate of different EFW cut-offs on routine ultrasound examination at 35 + 0 to 36 + 6 weeks' gestation. Fourth, to propose a two-stage strategy for identifying pregnancies with a LGA fetus that may benefit from iatrogenic delivery during the 38^th gestational week.

METHODS

This was a retrospective study. First, data from 21 989 singleton pregnancies that had undergone routine ultrasound examination at 31 + 0 to 33 + 6 weeks' gestation and 45 847 that had undergone routine ultrasound examination at 35 + 0 to 36 + 6 weeks were used to compare the predictive performance of EFW and AC for a LGA neonate with birth weight > 90^th and > 97^th percentiles born at ≥ 37 weeks' gestation. Second, data from 14 497 singleton pregnancies that had undergone routine ultrasound examination at 35 + 0 to 36 + 6 weeks' gestation and had a previous scan at 30 + 0 to 34 + 6 weeks were used to determine, through multivariable logistic regression analysis, whether addition of growth velocity, defined as the difference in EFW Z-score or AC Z-score between the early and late third-trimester scans divided by the time interval between the scans, improved the performance of EFW at 35 + 0 to 36 + 6 weeks in the prediction of delivery of a LGA neonate at ≥ 37 weeks' gestation. Third, in the database of the 45 847 pregnancies that had undergone routine ultrasound examination at 35 + 0 to 36 + 6 weeks' gestation, the screen-positive and detection rates for a LGA neonate born at ≥ 37 weeks' gestation and ≤ 10 days after the initial scan were calculated for different EFW percentile cut-offs between the 50^th and 90^th percentiles.

RESULTS

First, the areas under the receiver-operating characteristics curves (AUC) of screening for a LGA neonate were significantly higher using EFW Z-score than AC Z-score and at 35 + 0 to 36 + 6 than at 31 + 0 to 33 + 6 weeks' gestation (P < 0.001 for all). Second, the performance of screening for a LGA neonate achieved by EFW Z-score at 35 + 0 to 36 + 6 weeks was not significantly improved by addition of EFW growth velocity or AC growth velocity. Third, in screening by EFW > 90^th percentile at 35 + 0 to 36 + 6 weeks' gestation, the predictive performance for a LGA neonate born at ≥ 37 weeks' gestation was modest (65% and 46% for neonates with birth weight > 97^th and > 90^th percentiles, respectively, at a screen-positive rate of 10%), but the performance was better for prediction of a LGA neonate born ≤ 10 days after the scan (84% and 71% for neonates with birth weight > 97^th and > 90^th percentiles, respectively, at a screen-positive rate of 11%). Fourth, screening by EFW > 70^th percentile at 35 + 0 to 36 + 6 weeks' gestation predicted 91% and 82% of LGA neonates with birth weight > 97^th and > 90^th percentiles, respectively, born at ≥ 37 weeks' gestation, at a screen-positive rate of 32%, and the respective values of screening by EFW > 85^th percentile for prediction of a LGA neonate born ≤ 10 days after the scan were 88%, 81% and 15%. On the basis of these results, it was proposed that routine fetal biometry at 36 weeks' gestation is a screening rather than diagnostic test for fetal macrosomia and that EFW > 70^th percentile should be used to identify pregnancies in need of another scan at 38 weeks, at which those with EFW > 85^th percentile should be considered for iatrogenic delivery during the 38^th  week.

CONCLUSIONS

First, the predictive performance for a LGA neonate by routine ultrasonographic examination during the third trimester is higher if the scan is carried out at 36 than at 32 weeks, the method of screening is EFW than fetal AC, the outcome measure is birth weight > 97^th than > 90^th percentile and if delivery occurs within 10 days than at any stage after assessment. Second, prediction of a LGA neonate by EFW > 90^th percentile is modest and this study presents a two-stage strategy for maximizing the prenatal prediction of a LGA neonate. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.