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

Beta, J.; Khan, Naila Zaman; Khalil, Ahmed; Fiolna, M.; Ramadan, G.; Akolekar, Ranjit

doi:10.1002/uog.20279

Cited by 158 publications

(98 citation statements)

References 35 publications

(133 reference statements)

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“…Based on these findings, a positive association between GI and GL diets and gestational diabetes and gestational weight gain (GWG) has been hypothesised, which should protect against excessive GWG and macrosomia, both prevalent and relevant issues around the world (6,7) . Some studies have tried to test this hypothesis, though the literature shows inconclusive results, as discussed below.…”

mentioning

confidence: 99%

The association of dietary glycaemic index and glycaemic load with gestational weight gain and newborn birth weight

et al. 2019

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Diet during pregnancy is related to several maternal and infant health outcomes; however, the relationship between maternal dietary glycaemic index (GI) and glycaemic load (GL) and gestational weight gain (GWG) or newborn birth weight is controversial. The purpose of the present study was to investigate the relationship between maternal dietary GI and GL and GWG and birth weight. A cohort of adult pregnant women with usual obstetric risk was followed in Botucatu, SP, Brazil. Two 24-h dietary recalls were collected in each gestational trimester (<14, 24–27, 31–34 weeks), one in person and the other by telephone. GI and GL were determined using the software Nutrition Data System for Research. GWG was obtained from medical records and evaluated as the weekly GWG between the second and third gestational trimesters. Newborn birth weight z-score in relation to gestational age was evaluated according to Intergrowth-21st Project recommendations. A multiple linear regression model, adjusted for potential confounders, showed a one-point increase in the GI resulted in a mean decrease of 12·9 (95 % CI –21·48, –4·24) g in weekly GWG; GL was not associated with this outcome. The birth weight z-score was not associated with GI (P = 0·763) or GL (P = 0·317). In conclusion, in a cohort of pregnant women considered at usual risk for obstetric complications, maternal dietary GI was negatively associated with weekly GWG in the second and third gestational trimesters. No association was observed between GL and GWG, and neither GI nor GL was associated with birth weight z-score.

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confidence: 99%

The association of dietary glycaemic index and glycaemic load with gestational weight gain and newborn birth weight

et al. 2019

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“…If at 36 + 0 weeks' gestation there were no errors in the measurements of 306.5 mm for AC, 316.7 mm for HC and 65.8 mm for FL, EFW would be 2453 g, which corresponds to the 10 th percentile. An error resulting in underestimation in the measurement of AC by 11 The effect of errors in individual biometry measurements, in mm and SD units, on EFW at 36 + 0 weeks' gestation when true EFW is on the 10 th and 90 th percentiles (2453 g and 3086 g, respectively), with corresponding biometry measurements as outlined above, can be seen in Figure 2. In terms of SD units, which allow for a fair comparison of the three measures, errors in AC have the largest impact on EFW percentile and errors in HC have the smallest impact on EFW percentile.…”

Section: Resultsmentioning

confidence: 99%

“…About 85% of SGA neonates are born at term 6 and there is now good evidence that the predictive performance for a term SGA neonate is higher if, first, the method of screening is routine third-trimester ultrasonographic fetal biometry rather than selective ultrasonography based on maternal risk factors and serial measurements of symphysis-fundus height 7 , and, second, the routine scan is carried out at 35 + 0 to 36 + 6 weeks' gestation rather than at 31 + 0 to 33 + 6 weeks 8,9 . Similarly, large-for-gestational-age (LGA) neonates with birth weight > 90 th percentile are at increased risk of perinatal death, birth injury and adverse neonatal outcome 2,4,10,11 . Such risks could potentially be reduced by elective Cesarean section or early induction of labor to reduce the inevitable increase in fetal size with advancing gestational age [12][13][14] .…”

Section: Introductionmentioning

confidence: 99%

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

Wright

Smith³

et al. 2020

Ultrasound in Obstet & Gyne

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CONTRIBUTION What are the novel findings of this work?This study examines the impact of measurement errors in fetal head circumference, abdominal circumference and femur length on sonographic estimated fetal weight (EFW) and their effect on the prediction of small-(SGA) and large-(LGA) for-gestational-age fetuses.What are the clinical implications of this work? 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 on the prediction of SGA and LGA fetuses. ABSTRACTObjectives 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. ResultsErrors 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.

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“…The primary aim of detection of large fetuses is prevention of stillbirth, shoulder dystocia, maternal peripartum hemorrhage, injuries of both mother and neonate, cesarean section as well risk of maternal diabetes and metabolic syndrome in childhood [29]. In recent study Caradoux et al compared different strategies to predict macrosomia and LGA.…”

Section: Definitions Detection and Consequencesmentioning

confidence: 99%

Growth charts and prediction of abnormal growth — what is known, what is not known and what is misunderstood

Kajdy

Modzelewski²,

Herman³

et al. 2019

Ginekol Pol

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Objectives: Assessment of fetal growth has an important effect on perinatal morbidity and mortality. To understand what tool to choose best for a given population a basic knowledge of how growth charts are developed and used has to be acquired. For this reason, this literature review was performed. Material and methods:An extensive literature review aimed at identifying articles related to the development of growth assessment in both spectrums of abnormal fetal growth -large and small. The analyzed articles were chosen and presented to show both the historical aspects of growth assessment, current trends and future considerations.Results: Identification of both large and small fetuses and neonates is equally crucial. Definitions and methodology vary worldwide and there is an ongoing discussion on the best tool to choose for a given population. An important part of the debate is how to differentiate between the physiologically small fetus and the truly growth restricted fetus who is at risk of perinatal complication. Similarly, the diagnosis of a large fetus is important in prevention of perinatal complications and surgical deliveries. Many clinical settings still lack growth standards. conclusions: Birthweight for gestational age charts are biased for weight in preterm birth. Prediction and management of outcome cannot be based solely on fetal size. Small is not the only problem, we have to think large as well. A common misunderstanding in clinical practice is not using uniform charts in defining growth.

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

Cited by 158 publications

References 35 publications

The association of dietary glycaemic index and glycaemic load with gestational weight gain and newborn birth weight

The association of dietary glycaemic index and glycaemic load with gestational weight gain and newborn birth weight

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

Growth charts and prediction of abnormal growth — what is known, what is not known and what is misunderstood

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