Ultrasound prediction of fetal macrosomia in pregnancies complicated by diabetes mellitus: a systematic review and meta-analysis.

OBJECTIVES: To report the diagnostic accuracy of ultrasound in identifying fetuses with macrosomia in pregnancies complicated by gestational or pregestational diabetes. METHODS: Medline, Embase and Cochrane databases were searched. Inclusion criteria were singleton pregnancies complicated by diabetes undergoing third-trimester ultrasound evaluation. The index test was represented by ultrasound estimation of fetal macrosomia (estimated fetal weight EFW or abdominal circumference AC >90th or 95th percentile). Subgroup analyses were also performed. Sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio were computed using the hierarchical summary receiver-operating characteristics model. RESULTS: Twenty studies were included in the systematic review including 8,530 pregnancies complicated by diabetes. Ultrasound showed an overall moderate accuracy in identifying fetuses with macrosomia with a sensitivity of 71.2 % (95 % CI 63.1-78.2), a specificity of 88.6 % (95 % CI 83.9-92.0). The interval between ultrasound and birth of two weeks showed the highest sensitivity and specificity (71.6 %, 95 % CI 47.9-87.3 and 91.7, 95 % CI 86.2-95.5). EFW sensitivity and specificity were 76.6 % (95 % CI 70.1-82.3) and 82.9 % (95 % CI 80.9-84.8), while AC 84.8 % (95 % CI 78.2-90.0) and 73.7 % (95 % CI 71.0-76.4). CONCLUSIONS: Ultrasound demonstrates an overall good diagnostic accuracy in detecting fetal macrosomia in pregnancies with diabetes.

An innovative supervised longitudinal learning procedure of recurrent neural networks with temporal data augmentation: Insights from predicting fetal macrosomia and large-for-gestational age.

BACKGROUND: Longitudinal data in health informatics studies often present challenges due to sparse observations from each subject, limiting the application of contemporary deep learning for prediction. This issue is particularly relevant in predicting birthweight, a crucial factor in identifying conditions such as macrosomia and large-for-gestational age (LGA). Previous approaches have relied on empirical formulas for estimated fetal weights (EFWs) from ultrasound measurements and mixed-effects models for interim predictions. METHOD: The proposed novel supervised longitudinal learning procedure features a three-step approach. First, EFWs are generated using empirical formulas from ultrasound measurements. Second, nonlinear mixed-effects models are applied to create augmented sequences of EFWs, spanning daily gestational timepoints. This augmentation transforms sparse longitudinal data into a dense parallel sequence suitable for training recurrent neural networks (RNNs). A tailored RNN architecture is then devised to incorporate the augmented sequential EFWs along with non-sequential maternal characteristics. RESULTS: The RNNs are trained on augmented data to predict birthweights, which are further classified for macrosomia and LGA. Application of this supervised longitudinal learning procedure to the Successive Small-for-Gestational-Age Births study yields improved performance in classification metrics. Specifically, sensitivity, area under the receiver operation characteristic curve, and Youden's Index demonstrate enhanced results, indicating the effectiveness of the proposed approach in overcoming sparsity challenges in longitudinal health informatics data. CONCLUSIONS: The integration of mixed-effects models for temporal data augmentation and RNNs on augmented sequences shows effective in accurately predicting birthweights, particularly in the context of identifying excessive fetal growth conditions.

Ultrasonographic placental parameters at 11-13+6 weeks' gestation in the prediction of complications in pregnancy after assisted reproductive technology.

OBJECTIVE: To evaluate the performance of maternal factors, biophysical and biochemical markers at 11-13 + 6 weeks' gestation in the prediction of gestational diabetes mellitus with or without large for gestational age (GDM ± LGA) fetus and great obstetrical syndromes (GOS) among singleton pregnancy following in-vitro fertilisation (IVF)/embryo transfer (ET). MATERIALS AND METHODS: A prospective cohort study was conducted between December 2017 and January 2020 including patients who underwent IVF/ET. Maternal mean arterial pressure (MAP), ultrasound markers including placental volume, vascularisation index (VI), flow index (FI) and vascularisation flow index (VFI), mean uterine artery pulsatility index (mUtPI) and biochemical markers including placental growth factor (PlGF) and soluble fms-like tyrosine kinase-1 (sFlt-1) were measured at 11-13 + 6 weeks' gestation. Logistic regression analysis was performed to determine the significant predictors of complications. RESULTS: Among 123 included pregnancies, 38 (30.9%) had GDM ± LGA fetus and 28 (22.8%) had GOS. The median maternal height and body mass index were significantly higher in women with GDM ± LGA fetus. Multivariate logistic regression analysis demonstrated that in the prediction of GDM ± LGA fetus and GOS, there were significant independent contributions from FI MoM (area under curve (AUROC) of 0.610, 95% CI 0.492-0.727; p = 0.062) and MAP MoM (AUROC of 0.645, 95% CI 0.510-0.779; p = 0.026), respectively. CONCLUSION: FI and MAP are independent predictors for GDM ± LGA fetus and GOS, respectively. However, they have low predictive value. There is a need to identify more specific novel biomarkers in differentiating IVF/ET pregnancies that are at a higher risk of developing complications.

A simulation study to assess the potential benefits of MRI-based fetal weight estimation as a second-line test for suspected macrosomia.

OBJECTIVE: To simulate the outcomes of Boulvain's trial by using magnetic resonance imaging (MRI) for estimated fetal weight (EFW) as a second-line confirmatory imaging. STUDY DESIGN: Data derived from the Boulvain's trial and the study PREMACRO (PREdict MACROsomia) were used to simulate a 1000-patient trial. Boulvain's trial compared induction of labor (IOL) to expectant management in suspected macrosomia, whereas PREMACRO study compared the performance of ultrasound-EFW (US-EFW) and MRI-EFW in the prediction of birthweight. The primary outcome was the incidence of significant shoulder dystocia (SD). Cesarean delivery (CD), hyperbilirubinemia (HB), and IOL at < 39 weeks of gestation (WG) were selected as secondary outcomes. A subgroup analysis of the Boulvain's trial was performed to estimate the incidence of the primary and secondary outcomes in the true positive and false positive groups for the two study arms. Sensitivity, specificity, positive and negative predictive values (PPV, NPV) for the prediction of macrosomia by MRI-EFW at 36 WG were calculated, and a decision tree was constructed for each outcome. RESULTS: The PPV of US-EFW for the prediction of macrosomia in the PREMACRO trial was 56.3 %. MRI-EFW was superior to US-EFW as a predictive tool resulting in lower rates of induction for false-positive cases. Repeating Boulvain's trial using MRI-EFW as a second-line test would result in similar rates of SD (relative risk [RR]:0.36), CD (RR:0.84), and neonatal HB (RR:2.6), as in the original trial. Increasing the sensitivity and specificity of MRI-EFW resulted in a similar relative risk for SD as in Boulvain's trial, but with reduced rates of IOL < 39 WG, and improved the RR of CD in favor of IOL. We found an inverse relationship between IOL rate and incidence of SD for both US-EFW and MRI-EFW, although overall rates of IOL, CD, and neonatal HB would be lower with MRI-derived estimates of fetal weight. CONCLUSION: The superior accuracy of MRI-EFW over US-EFW for the diagnosis of macrosomia could result in lower rates of IOL without compromising the relative advantages of the intervention but fails to demonstrate a significant benefit to justify a replication of the original trial using MRI-EFW as a second-line test.

Prediction of large-for-gestational age at 36 weeks' gestation: two-dimensional ultrasound vs three-dimensional ultrasound vs magnetic resonance imaging.

OBJECTIVE: To compare the performance of two-dimensional ultrasound (2D-US), three-dimensional ultrasound (3D-US) and magnetic resonance imaging (MRI) at 36 weeks' gestation in predicting the delivery of a large-for-gestational-age (LGA) neonate, defined as birth weight ≥ 95th percentile, in patients at high and low risk for macrosomia. METHODS: This was a secondary analysis of a prospective observational study conducted between January 2017 and February 2019. Women with a singleton pregnancy at 36 weeks' gestation underwent 2D-US, 3D-US and MRI within 15 min for estimation of fetal weight. Weight estimations and birth weight were plotted on a growth curve to obtain percentiles for comparison. Participants were considered high risk if they had at least one of the following risk factors: diabetes mellitus, estimated fetal weight ≥ 90th percentile at the routine third-trimester ultrasound examination, obesity (prepregnancy body mass index ≥ 30 kg/m2) or excessive weight gain during pregnancy. The outcome was the diagnostic performance of each modality in the prediction of birth weight ≥ 95th percentile, expressed as the area under the receiver-operating-characteristics curve (AUC), sensitivity, specificity and positive and negative predictive values. RESULTS: A total of 965 women were included, of whom 533 (55.23%) were high risk and 432 (44.77%) were low risk. In the low-risk group, the AUCs for birth weight ≥ 95th percentile were 0.982 for MRI, 0.964 for 2D-US and 0.962 for 3D-US; pairwise comparisons were non-significant. In the high-risk group, the AUCs were 0.959 for MRI, 0.909 for 2D-US and 0.894 for 3D-US. A statistically significant difference was noted between MRI and both 2D-US (P = 0.002) and 3D-US (P = 0.002), but not between 2D-US and 3D-US (P = 0.503). In the high-risk group, MRI had the highest sensitivity (65.79%) compared with 2D-US (36.84%, P = 0.002) and 3D-US (21.05%, P < 0.001), whereas 3D-US had the highest specificity (98.99%) compared with 2D-US (96.77%, P = 0.005) and MRI (96.97%, P = 0.004). CONCLUSIONS: At 36 weeks' gestation, MRI has better performance compared with 2D-US and 3D-US in predicting birth weight ≥ 95th percentile in patients at high risk for macrosomia, whereas the performance of 2D-US and 3D-US is comparable. For low-risk patients, the three modalities perform similarly. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Predictive value and accuracy of prenatal four-dimensional color ultrasound for fetal abnormal development.

To investigate the value and accuracy of prenatal GE-E10 ultrasound Equipment in predicting fetal abnormal development. 160 pregnant women and women who received prenatal ultrasound examination were selected. Before delivery, all pregnant women were examined by conventional two-dimensional and four-dimensional (4D) ultrasound. 18 fetuses with abnormal development were detected by gold standard in 160 pregnant women. Sensitivity and specificity of two-dimensional color ultrasound in diagnosing fetal abnormal development were 78.38% and 82.60%. The sensitivity and specificity of 4D color ultrasound in diagnosing fetal abnormal development were 81.15% and 83.43%. ROC showed that the AUC (0.873) of 4D color ultrasound was higher than that of two-dimensional color ultrasound (0.827). The diagnostic efficiency of 4D ultrasound is greater. The accuracy, specificity and sensitivity of 4D color ultrasound in the diagnosis of fetal abnormal development is high, and it is valuable for prenatal screening of macrosomia and low birth weight.

Fetal heart biventricular diameter/foot length index as a diagnostic marker of fetal macrosomia in the second and third trimester of pregnancy.

PURPOSE: Fetal macrosomia may have serious effects on both mother and newborn, so it is important to correctly evaluate the fetal weight before delivery. Fetal routine biometry, height of the fundus of uterus, interventricular septal thickness seems to be very good but still not perfect. In our study the relation between fetal biventricular (AP) diameter and fetal foot length was elaborated in the 2nd and 3rd trimester of pregnancy. MATERIAL AND METHODS: The analyzed group (n = 423 fetuses) was divided into 2 subgroups: a control group (n = 109 fetuses) with normal biometry, normal heart anatomy and normal cardiac function, no extracardiac malformation, no extracardiac anomalies, gestational age ranged from 17.5 to 37.1 weeks of gestation, born at term with birth weight 3000-3600 g, and a study group (n = 314 fetuses) with gestational age 17.5-39.5 weeks. Among the study group there were 20 patients (n = 20 fetuses) with macrosomia defined as a neonatal birth weight of greater than or equal to 4000 g. The control group was used to generate normograms on fetal AP, foot length and AP/Foot Index. The Statistica 13.3 and Excel 365 software were used to calculate the sensitivity, specificity, positive predictive value and negative predictive values. RESULTS: In control group, the mean biventricular fetal heart (AP) measurement was 23 mm (12.9 mm-38 mm), the mean foot length was 43 mm (24 mm-71 mm), and the mean AP/Foot Index was 0.52 (0.40-0.65). The value of the AP/Foot Index in the second trimester of the control group was 0.53, whereas the AP/Foot Index in the third trimester of pregnancy was 0.51. The use of standard fetal biometry resulted in the prediction of macrosomia in 20%, whereas the AP/Foot index in addition to standard fetal biometry enabled the detection of 65% of macrosomia. CONCLUSIONS: The AP/Foot Index higher than 0.52 has greater sensitivity and negative predictive value to detect macrosomia compared to standard ultrasound fetal biometry.

ULTRASOUND DIAGNOSIS OF MACROSOMIA AMONG WOMEN WITH GESTATIONAL DIABETES - REVIEW OF THE LITERATURE.

Pregnancies burdened with gestational diabetes (GDM) are more likely to end in birth of a macrosomic child, where the frequency of operative termination of pregnancy is more common, accompanied with more complications and injuries of both mother and child in comparison to the general population. The need to calculate fetal weight right before delivery has led to the development of numerous methods for greater estimation accuracy. We reviewed the related literature from 1980 to 2020, using the terms macrosomia, ultrasound assessment, gestational diabetes, and relevant articles were considered in preparation of this article. The most frequently used methods are based on two-dimensional ultrasound measurements of individual fetal biometric parameters and their combination in a mathematical regression model. Some methods involve the addition of other mother and child conditions to increase reliability of the method in recognizing macrosomia. In daily work, especially with pregnant women suffering from GDM, it is necessary to have reliable data on the estimated fetal weight before making the correct clinical decision on how to terminate the pregnancy. In this regard, we bring a review of the literature related to the assessment of fetal macrosomia, especially in women with GDM.

Prediction of large-for-gestational-age infant by fetal growth charts and hemoglobin A1c level in pregnancy complicated by pregestational diabetes.

OBJECTIVES: To compare the ability of three fetal growth charts (Fetal Medicine Foundation (FMF), Hadlock and National Institutes of Child Health and Human Development (NICHD) race/ethnicity-specific) to predict large-for-gestational age (LGA) at birth in pregnant individuals with pregestational diabetes, and to determine whether inclusion of hemoglobin A1c (HbA1c) level improves the predictive performance of the growth charts. METHODS: This was a retrospective analysis of individuals with Type-1 or Type-2 diabetes with a singleton pregnancy that resulted in a non-anomalous live birth. Fetal biometry was performed between 28 + 0 and 36 + 6 weeks of gestation. The primary exposure was suspected LGA, defined as estimated fetal weight ≥ 90th percentile using the Hadlock (Formula C), FMF and NICHD growth charts. The primary outcome was LGA at birth, defined as birth weight ≥ 90th percentile, using 2017 USA natality reference data. The performance of the three growth charts to predict LGA at birth, alone and in combination with HbA1c as a continuous measure, was assessed using the area under the receiver-operating-characteristics curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value. RESULTS: Of 358 assessed pregnant individuals with pregestational diabetes (34% with Type 1 and 66% with Type 2), 147 (41%) had a LGA infant at birth. Suspected LGA was identified in 123 (34.4%) by the Hadlock, 152 (42.5%) by the FMF and 152 (42.5%) by the NICHD growth chart. The FMF growth chart had the highest sensitivity (77% vs 69% (NICHD) vs 63% (Hadlock)) and the Hadlock growth chart had the highest specificity (86% vs 76% (NICHD) and 82% (FMF)) for predicting LGA at birth. The FMF growth chart had a significantly higher AUC (0.79 (95% CI, 0.74-0.84)) for LGA at birth compared with the NICHD (AUC, 0.72 (95% CI, 0.68-0.77); P < 0.001) and Hadlock (AUC, 0.75 (95% CI, 0.70-0.79); P < 0.01) growth charts. Prediction of LGA improved for all three growth charts with the inclusion of HbA1c measurement in comparison to each growth chart alone (P < 0.001 for all); the FMF growth chart remained more predictive of LGA at birth (AUC, 0.85 (95% CI, 0.81-0.90)) compared with the NICHD (AUC, 0.79 (95% CI, 0.73-0.84)) and Hadlock (AUC, 0.81 (95% CI, 0.76-0.86)) growth charts. CONCLUSIONS: The FMF fetal growth chart had the best predictive performance for LGA at birth in comparison with the Hadlock and NICHD race/ethnicity-specific growth charts in pregnant individuals with pregestational diabetes. Inclusion of HbA1c improved further the prediction of LGA for all three charts. © 2022 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

The birth weight of macrosomia influence the accuracy of ultrasound estimation of fetal weight at term.

OBJECTIVE: To evaluate and analyze the accuracy of ultrasound estimation of the fetal weight of Macrosomia at term. METHOD: The instruments used were α6(Aloka; Japan) color Doppler ultrasound imagers, and vinno 80 (feieno; China) with a frequency of 3.5 MHz. The formula used to calculate the estimated fetal birth weight (EFW) was that proposed by Hadlock et al. (Hadlock 2). The biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur length (FL) measurements were performed strictly following the practice guidelines. Detailed measurement standards are shown in the figure and the table in the text. Macrosomia is typically defined as a birth weight above the 90th percentile for gestational age or >4000 g.Two indexes were used to calculate the error between EFW and birth weight (BW): Simple error (SE = BW - EFW); Absolute percentage error (APE, which reflects this percentage in absolute value, percentage error [PE = SE/BW] × 100). In order to better evaluate the measurement results, we made the following definitions: 1. When APE > 15%, the measurement deviation is significant. 2. The ratio of those cases with APE > 15% to the total number of cases measured by a sonographer was greater than 20%, indicating that the sonographer was prone to significant measurement deviation. RESULT: A total of 374 cases were analyzed. The mean maternal age was 31.48 (±15.93) years. Each pregnant woman carries only one fetus. The mean gestational age at delivery was 39.93 (±0.84) weeks. There were 245 male infants (65.5%), 129 female infants (34.5%), 214 cesarean section (57.2%), and 160 vaginal delivery (42.7%). 339 cases (90.64%) were estimated to be lower than the actual BW. The estimated weight was higher than the actual weight in 35 cases, accounting for 9.36%.The APE>15% in 56 cases, accounting for 14.97%. The accuracy of estimated fetal weight was closely related to the BW of the fetus and had no significant correlation with the seniority of the physician, the gender of the fetus, and the fetal position. CONCLUSION: Studies on macrosomia have shown that the BW of macrosomia tends to be underestimated, which is also reflected in the results of this study. The accuracy of estimated fetal weight still needs to be improved. Our study found that the accuracy of estimated fetal weight was closely related to the BW of the fetus and had no significant correlation with the seniority of the physician, the gender of the fetus, and the fetal position. The correlation between the section and calculation formula on the measurement accuracy needs to be studied. Through systematic data analysis, we can find the doctors whose measurements are relatively inaccurate in our department and carry out targeted quality control to improve the measurement accuracy.

Effective Macrosomia Prediction Using Random Forest Algorithm.

(1) Background: Macrosomia is prevalent in China and worldwide. The current method of predicting macrosomia is ultrasonography. We aimed to develop new predictive models for recognizing macrosomia using a random forest model to improve the sensitivity and specificity of macrosomia prediction; (2) Methods: Based on the Shandong Multi-Center Healthcare Big Data Platform, we collected the prenatal examination and delivery data from June 2017 to May 2018 in Jinan, including the macrosomia and normal-weight newborns. We constructed a random forest model and a logistic regression model for predicting macrosomia. We compared the validity and predictive value of these two methods and the traditional method; (3) Results: 405 macrosomia cases and 3855 normal-weight newborns fit the selection criteria and 405 pairs of macrosomia and control cases were brought into the random forest model and logistic regression model. On the basis of the average decrease of the Gini coefficient, the order of influencing factors was: interspinal diameter, transverse outlet, intercristal diameter, sacral external diameter, pre-pregnancy body mass index, age, the number of pregnancies, and the parity. The sensitivity, specificity, and area under curve were 91.7%, 91.7%, and 95.3% for the random forest model, and 56.2%, 82.6%, and 72.0% for logistic regression model, respectively; the sensitivity and specificity were 29.6% and 97.5% for the ultrasound; (4) Conclusions: A random forest model based on the maternal information can be used to predict macrosomia accurately during pregnancy, which provides a scientific basis for developing rapid screening and diagnosis tools for macrosomia.

Fetal front-abdominal wall thickness in the second trimester as a predictor of abnormal fetal growth.

OBJECTIVES: Worldwide, approximately 9% of infants have a birth weight ≥4000 g, who are defined as fetal macrosomia, with wide variations between countries. Another form of abnormal fetal growth is fetal growth restriction. Infants with low birth weight (LBW) for their gestational age are primarily categorized as either small for gestational age (SGA) or fetal (intrauterine) growth restriction (FGR). All forms of abnormal fetal growth have high morbidity rates of neonatal. Therefore, diagnosis of abnormal fetal growth as early as possible is crucial for optimal clinical care. The measurement of fetal front-abdominal wall thickness (FAWT) is an easy examination. We conducted this study, wondering whether FAWT can predict birth weight or can determine LGA/macrosomia and/or LBW infants in advance. METHODS: This longitudinal cohort study was done in a tertiary center between September 2016 and September 2019. In total, 768 pregnant women with who attended our clinic for oral glucose tolerance test (OGTT) screening between the 26th and 28th weeks of gestation were included in this study. A total of 768 patients were evaluated in the present study. However, 186 of them were excluded in the follow-up of the study because they met the exclusion criteria or they gave birth in another hospital. Eventually, 582 pregnant women were included, with 57 in the LBW group, 461 in the AGA group, and 64 in the LGA group. In addition, 55 fetuses in the LGA group were determined to be macrosomic (birth weight > 4000 g). The FAWT and classic fetal biometric measurements, such as BPD, AC, FL, and EFW, were compared between the AGA group and the macrosomic infants. Statistical analysis was performed to compare the AGA group and the macrosomic infants group. There were no macrosomic infants in the AGA group, so this was used as the control group. RESULTS: There were no significant differences between the groups for maternal age, gravidity, parity, gestational age on the day of the examination, and gestational age at birth. The mean FAWT was significantly thinner in the SGA group than in the appropriate for gestational age (AGA) group (3.4 versus 3.9 mm, respectively, p < .001), while it was significantly thicker in the LGA group than in the AGA group (4.1 versus 3.9 mm, respectively, p < .001). CONCLUSION: FAWT measurement can provide more information and may be more sensitive toward fetal nutrition and growth than the AC value during the second trimester. Some benefits can be gained through the measurement of FAWT at the end of the second trimester. FAWT measurements can be used in obstetrical practice with a similar performance in predicting the LGA and macrosomic infant like AC and EFW.

Influence of Sonographic Fetal Weight Estimation Inaccuracies in Macrosomia on Perinatal Outcome.

OBJECTIVE: To evaluate the influence of inaccurate sonographic fetal weight estimation in macrosomia on the mode of delivery and neonatal outcome (NO). METHODS: In 14 633 pregnancies between 2002 and 2016, this retrospective study evaluated the association between sonographic fetal weight estimation, true birth weight (BW), mode of delivery (primary cesarean section [pCS], secondary cesarean section, vaginal delivery, and operative vaginal delivery rates) and NO parameters (5-min Apgar < 7, pH < 7.1, neonatal intensive care unit [NICU] admission, shoulder dystocia). Singleton pregnancies > 37 + 0 weeks with ultrasound-estimated fetal weight (EFW) within 7 days before delivery were included. The study population was divided into four groups: Group 1 (false-negative): EFW < 4000 g/BW ≥ 4000 g; Group 2 (true-positive): EFW ≥ 4000 g/BW ≥ 4000 g; Group 3 (false-positive): EFW ≥ 4000 g/BW < 4000 g; and Group 4 (true-negative): EFW < 4000 g/BW < 4000 g. RESULTS: As expected, the highest secondary cesarean section (sCS) rate was found in Group 2 (true-positive) (30.62 %), compared with only 17.68 % in Group 4 (true-negative). The sCS rate in the false-positive Group 3 was significantly higher (28.48 %) in comparison with the false-negative Group 1 (21.22 %; OR 1.48; 95 % CI, 1.16 to 1.89; P = 0.002). In comparison with the true-negative Group 4, univariate analyses showed significantly higher rates for sCS in all other groups: odds ratio (OR) 2.06 for Group 2 (95 % CI, 1.74 to 2.42; P < 0.001), 1.85 for Group 3 (95 % CI, 1.54 to 2.22, P < 0.001), and 1.25 for Group 1 (95 % CI, 1.05 to 1.49; P < 0.01). No significant differences were found for NO between Groups 1 and 3 for the parameters 5-min Apgar < 7 (P = 0.75), pH < 7.1 (P = 0.28), or NICU admission (P = 0.54). However, there was a significantly higher chance for shoulder dystocia in Group 1 compared with Group 3 (OR 4.58; 95 % CI, 1.34 to 24.30; P = 0.008). CONCLUSION: Sonographic EFW inaccuracies in fetal macrosomia appear to have a greater impact on the mode of delivery than birth weight itself. Underestimation of fetal weight may be associated with a higher probability of shoulder dystocia.

False diagnosis of small for gestational age and macrosomia - clinical and sonographic predictors.

PURPOSE: To investigate clinical and sonographic features associated with sonographic accuracy for the prediction of small for gestational age (SGA) and macrosomia at birth. METHODS: The database of a tertiary medical center was retrospectively searched for women who gave birth at term to a singleton healthy neonate in 2007-2014 and underwent sonographic estimated fetal weight (sEFW) evaluation within 3 d before delivery. Fetal growth restriction (FGR) and SGA were defined as sEFW or birth weight <10th percentile for gestational age; macrosomia was defined as birth weight >4000 grams. Data on maternal age, parity, gestational age, fetal gender, presentation, placental location, diabetes, hypertension, and oligo/polyhydramnios were compared between pregnancies with a false-negative and false-positive diagnosis of SGA or macrosomia. RESULTS: Of the 5425 fetal weight evaluations, 254 (4.7%) deviated by >15% from the actual birth weight. Nulliparity, absence of diabetes, neonatal female gender, anterior placenta, lower birth weight, and oligohydramnios were associated with a high deviation. We identified 482 SGA neonates (8.9%) and 633 macrosomic neonates (11.7%). A false-positive diagnosis of FGR was associated with oligohydramnios, absence of diabetes, and posterior placenta, and a false-negative diagnosis, with older maternal age, nulliparity, and male gender. A false-positive diagnosis of macrosomia was associated with older maternal age, multiparity, polyhydramnios, anterior placenta, and lack of hypertensive complications, and a false-negative diagnosis, with diabetes, hypertension, oligohydramnios, and vertex presentation. CONCLUSION: The accuracy of sEFW is affected by clinical and sonographic pregnancy characteristics. Further analyses should focus on improving accuracy especially at the fetal weight extremes.

Fetal magnetic resonance imaging at 36 weeks predicts neonatal macrosomia: the PREMACRO study.

BACKGROUND: Large-for-gestational-age fetuses are at increased risk of perinatal morbidity and mortality. Magnetic resonance imaging seems to be more accurate than ultrasound in the prediction of macrosomia; however, there is no well-powered study comparing magnetic resonance imaging with ultrasound in routine pregnancies. OBJECTIVE: This study aimed to prospectively compare estimates of fetal weight based on 2-dimensional ultrasound and magnetic resonance imaging with actual birthweights in routine pregnancies. STUDY DESIGN: From May 2016 to February 2019, women received counseling at the 36-week clinic. Written informed consent was obtained for this Ethics Committee-approved study. In this prospective, single-center, blinded study, pregnant women with singleton pregnancies between 36 0/7 and 36 6/7 weeks' gestation underwent both standard evaluation of estimated fetal weight with ultrasound according to Hadlock et al and magnetic resonance imaging according to the formula developed by Baker et al, based on the measurement of the fetal body volume. Participants and clinicians were aware of the results of the ultrasound but blinded to the magnetic resonance imaging estimates. Birthweight percentile was considered as the gold standard for the ultrasound and magnetic resonance imaging-derived percentiles. The primary outcome was the area under the receiver operating characteristic curve for the prediction of large-for-gestation-age neonates with birthweights of ≥95th percentile. Secondary outcomes included the comparative prediction of large-for-gestation-age neonates with birthweights of ≥90th, 97th, and 99th percentiles and small-for-gestational-age neonates with birthweights of ≤10th, 5th, and 3rd percentiles for gestational age and maternal and perinatal complications. RESULTS: Of 2914 women who were initially approached, results from 2378 were available for analysis. Total fetal body volume measurements were possible for all fetuses, and the time required to perform the planimetric measurements by magnetic resonance imaging was 3.0 minutes (range, 1.3-5.6). The area under the receiver operating characteristic curve for the prediction of a birthweight of ≥95th percentile was 0.985 using prenatal magnetic resonance imaging and 0.900 using ultrasound (difference=0.085, P<.001; standard error, 0.020). For a fixed false-positive rate of 5%, magnetic resonance imaging for the estimation of fetal weight detected 80.0% (71.1-87.2) of birthweight of ≥95th percentile, whereas ultrasound for the estimation of fetal weight detected 59.1% (49.0-68.5) of birthweight of ≥95th percentile. The positive predictive value was 42.6% (37.8-47.7) for the estimation of fetal weight using magnetic resonance imaging and 35.4% (30.1-41.1) for the estimation of fetal weight using ultrasound, and the negative predictive value was 99.0% (98.6-99.3) for the estimation of fetal weight using magnetic resonance imaging and 98.0% (97.6-98.4) for the estimation of fetal weight using ultrasound. For a fixed false-positive rate of 10%, magnetic resonance imaging for the estimation of fetal weight detected 92.4% (85.5-96.7) of birthweight of ≥95th percentile, whereas ultrasound for the estimation of fetal weight detected 76.2% (66.9-84.0) of birthweight of ≥95th percentile. The positive predictive value was 29.9% (27.2-32.8) for the estimation of fetal weight using magnetic resonance imaging and 26.2% (23.2-29.4) for the estimation of fetal weight using ultrasound, and the negative predictive value was 99.6 (99.2-99.8) for the estimation of fetal weight using magnetic resonance imaging and 98.8 (98.4-99.2) for the estimation of fetal weight using ultrasound. The area under the receiver operating characteristic curves for the prediction of large-for-gestational-age neonates with birthweights of ≥90th, 97th, and 99th percentiles and small-for-gestational-age neonates with birthweights of ≤10th, 5th, and 3rd percentiles was significantly larger in prenatal magnetic resonance imaging than in ultrasound (P<.05 for all). CONCLUSION: At 36 weeks' gestation, magnetic resonance imaging for the estimation of fetal weight performed significantly better than ultrasound for the estimation of fetal weight in the prediction of large-for-gestational-age neonates with birthweights of ≥95th percentile for gestational age and all other recognized cutoffs for large-for-gestational-age and small-for-gestational-age neonates (P<.05 for all).

Obstetric consequences of a false-positive diagnosis of large-for-gestational-age fetus.

OBJECTIVE: To compare delivery outcomes between true-positive (TP) and false-positive (FP) large-for-gestational-age (LGA) fetuses, appropriate-for-gestational-age (AGA) fetuses, and false-negative (FN) LGA fetuses. METHODS: Retrospective cohort study of singleton pregnancies at risk for macrosomia without contraindication to vaginal delivery, receiving an ultrasound scan at 34-37 weeks of pregnancy. RESULTS: In all, 430 pregnancies were included: 155 TP LGA, 87 FP LGA, 177 AGA and 11 FN LGA newborns. Cesarean section rate during labor was significantly higher in FP LGA than in AGA (19% vs. 8.7%) but not significantly different between FP LGA and TP LGA (19% vs. 32.4%). Median birth weight z score was significantly higher in TP LGA (1.9) compared with the FP LGA and AGA (0.91 and 0.84, respectively), whereas no significant differences were found between FP LGA and AGA. Admission to a neonatal intensive care unit was significantly more frequent in TP LGA than AGA, whereas shoulder dystocia, postpartum hemorrhage, and third- to fourth-degree perineal tears were similar between the different groups. CONCLUSION: A false-positive diagnosis of LGA fetus is associated with a significant increase of cesarean section during labor. Therefore, a suspicious ultrasound may result in reduction of the clinical threshold for the diagnosis of abnormal labor.

Accelerated fetal growth velocity across the third trimester is associated with increased shoulder dystocia risk among fetuses who are not large-for-gestational-age: A prospective observational cohort study.

OBJECTIVE: To investigate whether fetuses with accelerated third trimester growth velocity are at increased risk of shoulder dystocia, even when they are not large-for-gestational-age (LGA; estimated fetal weight (EFW) >95th centile). METHODS: Fetal growth velocity and birth outcome data were prospectively collected from 347 nulliparous women. Each had blinded ultrasound biometry performed at 28 and 36 weeks' gestation. Change in EFW and abdominal circumference (AC) centiles between 28-36 weeks were calculated, standardised over exactly eight weeks. We examined the odds of shoulder dystocia with increasing EFW and AC growth velocities among women with 36-week EFW ≤95th centile (non-LGA), who went on to have a vaginal birth. We then examined the relative risk (RR) of shoulder dystocia in cases of accelerated EFW and AC growth velocities (>30 centiles gained). Finally, we compared the predictive performances of accelerated fetal growth velocities to 36-week EFW >95th centile for shoulder dystocia among the cohort planned for vaginal birth. RESULTS: Of the 226 participants who had EFW ≤95th centile at 36-week ultrasound and birthed vaginally, six (2.7%) had shoulder dystocia. For each one centile increase in EFW between 28-36 weeks, the odds of shoulder dystocia increased by 8% (odds ratio (OR [95% Confidence Interval (CI)]) = 1.08 [1.04-1.12], p<0.001). For each one centile increase in AC between 28-36 weeks, the odds of shoulder dystocia increased by 9% (OR[95%CI] = 1.09 [1.05-1.12], p<0.001). When compared to the rest of the cohort with normal growth velocity, accelerated EFW and AC velocities were associated with increased relative risks of shoulder dystocia (RR[95%CI] = 7.3 [1.9-20.6], p = 0.03 and 4.8 [1.7-9.4], p = 0.02 respectively). Accelerated EFW or AC velocities predicted shoulder dystocia with higher sensitivity and positive predictive value than 36-week EFW >95th centile. CONCLUSIONS: Accelerated fetal growth velocities between 28-36 weeks' gestation are associated with increased risk of shoulder dystocia, and may predict shoulder dystocia risk better than the commonly used threshold of 36-week EFW >95th centile.

Abnormal Fetal Growth: Small for Gestational Age, Fetal Growth Restriction, Large for Gestational Age: Definitions and Epidemiology.

Abnormal fetal growth (growth restriction and overgrowth) is associated with perinatal morbidity, mortality, and lifelong risks to health. To describe abnormal growth, "small for gestational age" and "large for gestational age" are commonly used terms. However, both are statistical definitions of fetal size below or above a certain threshold related to a reference population, rather than referring to an abnormal condition. Fetuses can be constitutionally small or large and thus healthy, whereas fetuses with seemingly normal size can be growth restricted or overgrown. Although golden standards to detect abnormal growth are lacking, understanding of both pathologic conditions has improved significantly.

Ultrasound Diagnosis of the Small and Large Fetus.

Antenatal imaging is crucial in the management of high-risk pregnancies. Accurate dating relies on acquisition of reliable and reproducible ultrasound images and measurements. Quality image acquisition is necessary for assessing fetal growth and performing Doppler measurements to help diagnose pregnancy complications, stratify risk, and guide management. Further research is needed to ascertain whether current methods for estimating fetal weight can be improved with 3-dimensional ultrasound or magnetic resonance imaging; optimize dating with late initiation of prenatal care; minimize under-diagnosis of fetal growth restriction; and identify the best strategies to make ultrasound more available in low-income and middle-income countries.