Fetal Macrosomia Uptodate

Fetal macrosomia Authors: Jacques S Abramowicz, MD, FACOG, FAIUM Jennifer T Ahn, MD, FACOG Section Editor: Deborah Levine, MD Deputy Editor: Vanessa A Barss, MD, FACOG

All topics are updated updated as new evidence evidence becomes becomes available available and our peer our peer review process is complete. Literature review current through: Mar through: Mar 2017. | This topic last updated: Feb updated: Feb 02, 2017. INTRODUCTION — Fetal macrosomia is associated with an increased risk of several maternal and newborn complications. This topic will review the definition, prevalence, significance, significance, risk factors, f actors, etiology, and diagnosis of macrosomia. Obstetric and pediatric management are discussed separately. (See "Shoulder dystocia: Risk factors and planning delivery of at risk pregnancies" and "Large for gestational age newborn" .) DEFINITION — Macrosomia refers to growth beyond a specific threshold, regardless regardless of gestational age. In developed countries, the most commonly used threshold is weight above 4500 g (9 lb 15 oz), but weight above 4000 g (8 lb 13 oz) or 10 lb (4536 g) are also commonly used [1-4 1-4]]. A grading system has also been suggested: grade 1 for infants 4000 to 4499 g, grade 2 for 4500 to 4999 g, and grade 3 for over 5000 g [5]. This system is useful at term for decision-making decision-making regarding operative delivery. These thresholds are not based upon population statistics, where normal weight is typically defined as between the 10 th and 90th percentile for gestational age (assuming a normal population distribution), distribution), and are not useful for identifying the preterm macrosomic fetus. Using a statistical approach, any f etus/infant weighing weighing th >90 percentile for gestational age is considered large for gestational age. The following table shows the 5 th, 10th, 50th, 90th, and 95th percentile birth weights for gestational ages 24 to 42 weeks in the United States (table 1) 1). Some researchers prefer to use the 95 th percentile as the threshold for macrosomia as it corresponds to 1.90 standard deviations (SD) above the mean and defines 90 percent of the population as normal weight. Others use the 97.75 th percentile, which corresponds to 1.96 SD above the mean and defines 95 percent of the population as normal weight. The use of contemporary country-specific percentile tables is advisable when interpreting estimated fetal and newborn weight, particularly in the developing world. Newborn weights have increased over the past few decades, thus making older tables obsolete [6,7 6,7]]. In addition, some older tables (eg, Lubchenco) excluded, by choice, African-American, African-American, Asian, and Native Native American infants infants [8]. Racial and ethnic differences influence birth weight and also should be considered when interpreting estimated fetal and newborn weight [9-11 9-11]].

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prevalence of birth of infants ≥4000 g is PREVALENCE — The worldwide prevalence approximately 9 percent and approximately 0.1 percent for weight ≥5000 g, with wide variations among countries [12 12]]. In the United States, 8 percent of live born infants weigh ≥4000 g and 1.1 percent weigh more >4500 g [13 13]]. The prevalence of birth weight ≥4000 g in developing countries is typically 1 to 5 percent but ranges from 0.5 to 14.9 percent [14 14]]. SIGNIFICANCE — The risk of adverse outcome increases along a continuum based on the degree of macrosomia: At birth weights of 4000 to 4499 g, labor abnormalities and newborn complications begin to increase [15 15]]. At birth weights of 4500 to 4999 g, maternal and newborn morbidity further increases. At birth weights ≥5000 g, t he risk of stillbirth and neonatal mortality increases. For this reason, the presence of macrosomia is an important factor to consider in decision-making during delivery (eg, whether to use forceps or vacuum, whether to proceed to cesarean delivery). (See "Operative vaginal delivery" and "Shoulder dystocia: Risk factors and planning delivery of at risk pregnancies"..) pregnancies" Specific risks include [16-23 16-23]]: ●Maternal: •Protracted or arrested labor •Operative vaginal delivery •Cesarean delivery •Genital tract lacerations (vaginal, third-degree third -degree and fourth-degree f ourth-degree perineal) perineal) •Postpartum hemorrhage •Postpartum hemorrhage •Uterine rupture Macrosomia may be a greater obstetric hazard for women in developing countries where undernutrition during youth can inhibit complete pelvic growth, pregnancy before the pelvis is fully developed is common, and facilities for operative delivery of women with obstructed labor are not consistently available available [24 24]]. ●Fetal: •Shoulder dystocia leading to birth trauma (brachial plexus injury, fracture) or asphyxia. This is the most common serious intrapartum concern, and is discussed in detail separately. (See "Shoulder dystocia: Risk factors and planning delivery of at risk pregnancies" and "Shoulde "Shoulderr dystocia: Intrapartum diagnosis, management, and outcome". outcome" .) ●Neonatal (see "Large for gestational age newborn", section on 'Neonatal complications')): complications' •Hypoglycemia •Respiratory problems •Polycythemia











●Childhood and beyond: •Obesity •Impaired glucose tolerance •Metabolic syndrome •Cardiac remodeling (increase in aorta intima-media intima -media thickness and left ventricular mass) RISK FACTORS — Risk factors for f or macrosomia are listed in the table t able (table 2) 2 ). Macrosomia may be related to constitutional factors (eg, familial trait, male sex, ethnicity), environmental factors (maternal diabetes, gestational weight gain, maternal obesity, prepregnancy body mass index >30 kg/m 2 [25 25]]), post-term gestation, or genetic abnormalities. The long-term consequences vary for t he different factors [26 26]]. It has been proposed that a common characteristic of these conditions is intermittent maternal, and thus fetal, hyperglycemia. The consequent release of insulin, insulin-like insulin-like growth factors, and growth hormone, among others, leads to increased fetal glycogen and fat deposition and, in turn, t urn, amplified fetal growth [27 27]]. Others have reported that increased size of the placenta early in pregnancy is associated with macrosomia [28 28]]. In a correctly dated pregnancy, macrosomia is usually related to constitutional factors, maternal diabetes (gestational or pregestational), pregestational), and/or maternal obesity/excessive obesity/excessive gestational weight gain. With W ith the increasing prevalence of overweight and obese pregnant women, maternal obesity may have a greater impact on the prevalence of macrosomia than maternal diabetes [29 29]]. In a retrospective study of the relative contribution contribution of prepregnancy prepregnancy weight and gestational diabetes to the prevalence of large for gestational age (LGA) infants, the prevalence of LGA among normal weight and obese women without gestational diabetes was 7.7 and 12.7 percent, respectively [30 30]]. For women with gestational diabetes, the prevalence of LGA for normal weight and obese women was almost twofold higher: 13.6 and 22.3 percent, respectively. These differences were statistically significant. PATHOLOGIC ETIOLOGIES — If constitutional constitutional factors, maternal diabetes, and/or maternal obesity/excessive gestational weight gain have been excluded or seem unlikely, then the possibility of one of the rare syndromes associated with accelerated fetal growth should be considered, particularly in the presence of one or more fetal structural anomalies anomalies [31 31]]. Consultation with a geneticist can be useful to help with differential diagnosis, prenatal diagnostic evaluation (eg, selection and interpretation of molecular testing), and patient counseling. Syndromes associated with fetal overgrowth include: ●Pallister -Killian -Killian ●Beckwith-Wiedemann ●Beckwith-Wiedemann (see "Beckwith-Wiedemann syndrome") syndrome" )











●Costello ●Weaver ●Macrocephaly ●Macrocephaly Cutis Marmorata Telangiectasia Congenita (M-CMTC) (M -CMTC) DIAGNOSIS — Two-dimensional ultrasound examination is the standard modality used for diagnosis of fetal macrosomia and large for gestational age. In the general obstetrical population, Hadlock's formula (encompassing head circumference, circumference, abdominal circumference, and femur length measurements) is more informative than other methods. (See 'Estimating fetal weight' below.) Macrosomia is best identified by an ultrasound scan at the gestational-age when a decision regarding regarding the clinical management of the patient needs to be made. Performing a single estimation at 29 to 34 weeks of gestation has very poor predictive value for birth weight at term; estimated fetal weight at this t his time can significantly underestimate birth weight, probably because of accelerated growth in the later part of the third trimester [32,33 32,33]]. As discussed below, the estimation of fetal weight is not precise at any gestational age, and accurately identifying clinically important deviations of fetal growth, whether excessively excessively large or excessively small, is particularly difficult. (See 'Diagnostic performance' below.) SONOGRAPHY Diagnostic performance performance — Fetal weight is calculated by integrating biometric measurements into a formula, given that weight cannot be measured directly. Since the fetus is an irregular, three-dimensional three-dimensional structure of varying density, the ability of any formula to predict fetal density or weight is limited. Approximately three dozen formulas for sonographic estimation of fetal weight have been proposed, attesting to t he inadequacy of all methods (table 3) 3) [34 34]]. These formulas use measurements of fetal body parts with regression analysis of the dimension of one or multiple fetal biometric parameters against gestational age and actual birth weight [35 35]]. Available formulas perform better for normal sized fetuses than for macrosomic ones [12,36-42 12,36-42]] and no formula is clearly superior [43 43]]. A 2005 review of 14 studies on the sonographic detection of macrosomia (≥4000) in general obstetrical populations reported widely varying results: sensitivity 12 to 75 percent, specificity 68 to 99 percent, and post-test probability after a positive test 17 to 79 percent; results for populations with a high prevalence of macrosomia were at the upper end of these ranges [12 12]]. The studies used a variety of methods for sonographic estimation of fetal weight and illustrate the difficulty in accurately diagnosing or excluding macrosomia. The diagnosis of macrosomia defined as ≥4500 g is even less accurate; the mean absolute percent error for infants weighing above 4500 g was 12.6 percent versus 8.4 percent if below 4500 g in one study, regardless of diabetic status [40 40]]. In another











Comparison of diagnostic methods is complicated because investigators have used different methodologies to obtain and analyze their data (eg, mean error, mean percent error, standard deviation, and proportion of estimate fetal weight within 10 percent of actual birth weight). For diagnosing macrosomia, the accuracy of the testing m ethod depends upon how well the test distinguishes macrosomic fetuses from those with a weight within the normal range. Thus, a receiver-operator receiver-operator characteristic curve is the ideal way to compare methods of fetal weight estimation, but it has not been used consistently in diagnostic studies. (See "Evaluating diagnostic diagnostic tests", section on 'Receiver operating characteristic curves'. curves' .) Another consideration consideration is that sonographic sonographic measurement measurement does not not permit accurate differentiation between between fetuses who are large because of intrinsic fetal (genetic) versus extrinsic environmental factors [44 44]], similar to the scenario with the "constitutionally small" versus "growth restricted" fetus. Adding to the confusion, confusion, the American American College of of Obstetricians and Gynecologists concluded that ultrasound is better at ruling out macrosomia than ruling it in, since ultrasound tends to overestimate fetal weight [15 15]], while others have concluded that a positive ultrasound result is more accurate for ruling in macrosomia than a negative result for ruling it out [45 45]]. Estimating fetal weight — Ultrasound examination typically involves measurement of multiple biometric parameters that are incorporated incorporated into a formula for calculating calculating estimated fetal weight (EFW). Most commonly, a combination of biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur length (FL) is used. The most popular formulas are Hadlock's [ 46,47 46,47]] and Warsof's [48 48]] with Shepard's modification [49 49]]. These formulas are included in most ultrasound equipment packages: ●Hadlock for mulas: mulas: Log10 BW = 1.3598 + 0.051 (AC) + 0.1844 (FL) – (FL) – 0.0037 0.0037 (AC X FL), or Log10 BW = 1.4787 + 0.001837 (BPD) 2 + 0.0458 (AC) + 0.158 (FL) – (FL) – 0.003343 0.003343 (AC X FL) ●Shepard formula: Log10 BW = -1.7492 + 0.166 (BPD) + 0.046 (AC) - (2.646 [AC X BPD] /100) Comparisons of these formulas concluded that the formula using BPD, FL and AC (second Hadlock formula) resulted in the best estimate of fetal weight, while the formula using only BPD and AC (Shepard formula) had the least accurate estimate [50,51 50,51]].











determined in two dimensions (image 1) 1) or by an elliptical estimate (image 2). 2). Manually tracing the abdominal circumference, however, is less accurate and should be avoided [54 54]] (see "Prenatal assessment of gestational age and estimated date of delivery", section on 'Abdominal circumference' circumference')). An AC >90th percentile or two to three weeks ahead of gestational age may be an early marker for development of macrosomia despite normal EFW. Assessment of an enlarged AC on ultrasound should prompt fetal re-evaluation in three to four weeks, especially in patients with diabetes. Predictions for absence or presence of macrosomia can generally be made after two successive scans that show an increased AC. If the AC remains remains <90th percentile, then performing more ultrasound examinations examinations does not increase predictive value [55 55]]. Adjusting EFW EFW for maternal weight, weight, maternal height, height, date of delivery, delivery, and presence of of diabetes yields better sensitivity and specificity than traditional unadjusted formulas, particularly in macrosomic fetuses f etuses [56,57 56,57]]. Some investigators investigators have combined ultrasonography ultrasonography with pregnancy-specific data (eg, parity, ethnicity, body mass index, maternal height, weight, and weight gain) to create nomograms for detecting fetal macrosomia, but these methods have not performed well consistently [58-60 58-60]]. Adjunctive techniques ●Serial measurements measurements – – Serial Serial measurements can be taken over time to create an individual growth curve specific to an individual fetus. This makes it possible to extrapolate from multiple points to predict birth weight, theoretically enhancing diagnostic accuracy. However, the superiority and cost-effectiveness of this approach have not been proven [61-63 61-63]]. ●Soft tissue measurements measurements – – The The majority of sonographic sonographic EFW formulas f ormulas do not take body composition into account. Because body composition can vary greatly, even in the fetus, significant significant variation in birth weight can occur among fetuses with similar biometric parameters. parameters. Ultrasound measurement measurement of subcutaneous fat may improve assessment of normal versus accelerated growth [64,65 64,65]]. Body fat accounts for 14 percent of the birth weight in neonates, but 46 percent of birth weight variance [64 64]], and is subject to major changes when conditions associated with accelerated growth are present. As an example, women women with poorly poorly controlled diabetes diabetes are at increased increased risk of of having a macrosomic infant with a large volume of subcutaneous fat (see 'Women with diabetes' below). Subcutaneous fat has been measured at the midhumerus [66,67 66,67]], shoulder [68 68]], abdominal wall [69-71 69-71]], thigh [70-74 70-74]], and peribuccal area [75-79 75-79]]. Prenatal sonographic evaluation evaluation of adipose tissue appears to have good correlation with postnatal skin fold measurements, measurements, although data are limited [77,80 77,80]]. An analysis of three studies with a total of 287 fetuses reported a high degree of accuracy in













tissue measurement performed better than estimated fetal weight for detection of macrosomia [77 77]]. Combinations of soft tissue measurements or other parameters (umbilical cord cross section, amniotic fluid volume) with estimated fetal weight may be more useful for predicting macrosomia than any method alone [78,79,82,83 78,79,82,83]]. ●Fetal volume measurement – measurement – The The sonographic measurements described above estimate weight using two-dimensional principles on a three-dimensional subject. Improvements in imaging technologies have helped alleviate this problem, leading to better weight estimation. Volumetric measurement measurement by two-dimensional two-dimensional ultrasound can be calculated using the following formula f ormula [34 34]]: EFW = (0.23718 X AC2 X FL) + (0.03312 X HC 3). When compared with the traditional calculation of EFW using Shepard or Hadlock formulas described above, this method had fewer systematic and absolute errors (mean percent error was 6.2). Three-dimensional (3D) ultrasound examination can improve sonographic estimates of fetal weight by providing more accurate assessment of fetal volume. In addition, better qualitative analysis of fetal soft tissue may be possible with 3D ultrasound, allowing for improved estimation of actual birth weight [84 84]]. Studies using 3D ultrasound for birth weight prediction have validated the technique, with most predictions within 10 percent of birth weight [85-88 85-88]]. The best approach for predicting macrosomia may be to combine 3D volumetric measurements (volume of upper arms, thigh, and abdomen) with two-dimensional (2D) measurements (formula = -1478.557 + 7.242 X thigh vol +13.309 X upper arm vol + 852.998 X log10 AC vol + 0.526 X BPD 3) [89,90 89,90]]. With combined measurements, the mean absolute percentage of error was 6.5 percent versus 10 to 15 percent with 2D ultrasound alone. ●Neural network – network – This This is a computerized model of a biologic neural system that can be "trained" by establishing connections between basic data (input: BPD, occipitofrontal diameter, diameter, AC, FL, gestational age, fetal position) and results (output: EFW) and constantly rectifying the relations. It is still investigational. Only two studies have been performed analyzing the value of artificial neural networks in the estimation of fetal f etal weight [91,92 91,92]]. •In one study, assuming a 10 percent error in macrosomia, the neural











study, a difference in HC/AC ≥50 mm predicted shoulder dystocia regardless of EFW, with an odds ratio of 7.3, 95% CI 1.6-33.3 [93 93]]. NONSONOGRAPHIC METHODS Maternal estimation — In several studies, a mother's estimate of her baby's weight has been reported to be as or more accurate than clinical or sonographic estimates (table 3) 3) [94-99 94-99]]. Most of these studies have been in parous women, in whom an increased risk of repeat macrosomic birth in subsequent pregnancies has been well documented [5,100 5,100]]. Maternal estimation has been used primarily to predict macrosomia during labor in women without a recent ultrasound examination. Physical examination — Fetal weight can be estimated clinically by simple palpation of the fetus through the maternal abdomen (eg, Leopold maneuvers) and/or by measurement measurement of fundal height (the distance between the superior aspect of t he symphysis pubis and the upper border of the uterine fundus). These assessments are performed with the woman supine and her bladder empty. Major factors that affect estimation of fetal weight by palpation include maternal habitus [101 101]], fetal position, amount of amniotic fluid, and, most importantly, the examiner's experience [38 38]]. For fundal height measurement, the fundal endpoint is more a matter of judgment than a well-defined well-defined point. Some clinicians prefer starting the measurement at the fundus, f undus, which tends to prevent "adjustments" to selection of a specific endpoint, which may occur when measuring from the symphysis. Although inexpensive, inexpensive, convenient, convenient, and easy to learn, learn, prospective prospective studies of symphysissymphysisfundal measurements combined with Leopold maneuvers showed sensitivities of only 10 to 43 percent and positive predictive values of 28 to 53 percent for detecting macrosomia (table 3) 3) [102 102]]. A review of a variety of clinical methodologies used to diagnose macrosomia macrosomia reported that these methods detected 34 to 68 percent of infants ≥4000 g, and the post-test post -test probability of macrosomia after a positive test was similar to positive predictive values reported by others [12 12]]. As would be expected, clinical diagnosis was more accurate (post-test probability of macrosomia after a positive test: 61 to 86 percent) in populations with a higher prevalence of macrosomia, such as postterm and diabetic pregnancies. Thus, the capacity for antepartum diagnosis diagnosis of fetal f etal











DIAGNOSIS IN SPECIAL SITUATIONS — The methods for detection of macrosomia described above are standardized for singleton, cephalic presenting, nondiabetic pregnancies. When special situations prevail, limitations in these formulas should be recognized [102 102]]. Overestimations and underestimations are more common in estimating weight in infants of diabetic mothers, multiple gestations, and breech fetuses. Women with diabetes — The growth pattern of fetuses of women with diabetes, especially when glycemic control has been poor, is different from t hat in fetuses of women without diabetes [44,105,106 44,105,106]]. Macrosomic infants of diabetic mothers have larger shoulders and greater amounts of body fat, decreased head-to-shoulder head-to-shoulder ratio, and increased skin folds in the upper extremities [107,108 107,108]]. Several studies have used this information in an attempt to t o predict the risk of shoulder dystocia in pregnancies complicated by diabetes, but no method has proven to be reliable [109-113 109-113]]. Since infants of women with diabetes are at greatest relative risk of shoulder dystocia, this population has been targeted for prenatal diagnosis of macrosomia. Ultrasound prediction of estimated fetal weight in fetuses of diabetic mothers tends to overestimate fetal weight since the formula is very sensitive to measurement of abdominal circumference (AC), and AC in particular is increased in these fetuses [114-119 114-119]]. As an example, approximately 50 percent of infants of diabetic mothers delivered by scheduled cesarean for sonographic estimated fetal fe tal weight ≥4250 g had a birth weight <4000 g in one study [120 120]]. Customized formulas for use in diabetic mothers have generally not been proven to be beneficial. A study comparing comparing three estimated fetal weight formulas formulas using multiple multiple parameters parameters versus prediction of birth weight by formulas using AC alone concluded that measurement measurement of AC was quicker and similarly accurate; all of the formulas were associated with an error of +/- 20 to 25 percent [121 121]]. Another study reported that AC th >70 percentile is predictive of poor glycemic control and increased risk of macrosomia [122 122]]. Based on these findings, the American Diabetes Association recommended the use of AC >75th percentile as a measure of glycemic control and risk for macrosomia in diabetic gravidas, as discussed at the Fifth International Workshop-Conference Workshop-Conference on Gestational Diabetes [123 123]]. They suggested less intensified management (eg, less frequent self-blood glucose monitoring, medical nutritional therapy alone [without











Multiple gestation — Singleton estimated fetal weight formulas used with multiple gestations tend to overestimate estimated fetal weight, particularly at weights less than 2500 g [125 125]], possibly due to distortion of the AC from overcrowding overcrowding [35 35]]. This is not clinically important for macrosomia screening since macrosomia is rare in multiple gestations. MANAGEMENT — Obstetrical and pediatric management are discussed separately. (See "Shoulder dystocia: Risk factors and planning delivery of at risk pregnancies" and "Operative vaginal delivery" and "Large for gestational age newborn"..) newborn" PREVENTION — For women with diabetes mellitus, avoiding hyperglycemia is a proven means of reducing the frequency of macrosomia. In two large randomized trials, treatment of gestational diabetes reduced the incidence of macrosomia by 50 to 60 percent (from 21 to 10 percent [126 126]] and from 14.3 to 5.9 percent [127 127]]). In women with pregestational diabetes, studies have noted that mean blood glucose levels need to be less than about 100 mg/dL (5.6 mmol/L) to achieve a macrosomia rate comparable to the nondiabetic pregnant population [128,129 128,129]] (See "Pregestationa "Pregestationall diabetes mellitus: Glycemic control during pregnancy" and "Gestational diabetes mellitus: Glycemic control and maternal prognosis". prognosis" .) For obese women, prepregnancy weight loss can reduce the risk of delivering a macrosomic infant (see "Obesity in pregnancy pregnancy:: Complication Complications s and maternal management",, section on 'Prepregnan management" ' Prepregnancy cy weight loss' loss')). Prepregnancy intervention is important because substantial weight loss is not safe during pregnancy and fetal growth acceleration is sometimes noted as early as t he first or early- to mid-second trimester [130 130]]. For women of normal weight, avoidance of excessive gestational weight gain can reduce the risk of macrosomia. macrosomia. (See "Weight gain and loss in pregnancy", section on 'Pregnancy outcomes in women who meet, exceed, or do not achieve IOM recommendations recommenda tions for gestational weight gain'. gain' .) SUMMARY AND RECOMMENDATIONS











●Macrosomia may be related to constitutional factors (eg, f amilial trait, male sex, ethnicity), environmental factors (maternal diabetes, maternal weight gain, maternal obesity, post-term gestation), or genetic abnormalities (syndromes (syndromes such as Pallister-Killian, Beckwith-Wiedemann, Beckwith-Wiedemann, etc). (See 'Risk factors' above and 'Pathologic etiologies' above.) ●Two-dimensional ●Two-dimensional ultrasound ultrasound examination is the standard modality used for diagnosis of macrosomia and LGA. Hadlock's formula (encompassing head circumference, circumference, abdominal abdominal circumference, and femur length measurements) measurements) has the highest predictive value in the nondiabetic population. An abdominal circumference >35 cm is also predictive of macrosomia, but no test no test is highly sensitive and specific (table 3) 3). (See 'Sonography' above.) ●For women with diabetes mellitus, avoiding hyperglycemia is a proven means of reducing the frequency of macrosomia. For obese women, prepregnancy weight loss can reduce the risk of delivering a macrosomic infant. For women of normal weight, avoidance of excessive gestational weight gain can reduce the risk of macrosomia. (See 'Prevention' above.) Use of UpToDate is subject to the Subscription and License Agreement . REFERENCES 1. Langer O, Berkus MD, Huff RW, Samueloff A. Shoulder dystocia: should the fetus weighing greater than or equal to 4000 grams be delivered by cesarean section? Am J Obstet Gynecol 1991; 165:831. 2. Modanlou HD, Dorchester WL, Thorosian A, Freeman RK. Macrosomia--maternal, Macrosomia--maternal, fetal, and neonatal implications. implications. Obstet Gynecol 1980; 55:420. 3. Boyd ME, Usher RH, McLean FH. Fetal macrosomia: prediction, risks, proposed management. Obstet Gynecol 1983; 61:715. 4. Menticoglou SM, Manning FA, Morrison I, Harman CR. Must macrosomic fetuses be delivered by a caesarean section? A review of outcome for 786 babies greater than or equal to 4,500 g. Aust N Z J Obstet Gynaecol 1992; 32:100. 5. Boulet SL, Alexander GR, Salihu HM, Pass M. Macrosomic births in the united states: determinants, outcomes, and proposed grades of risk. Am J Obstet Gynecol 2003; 188:1372. 6. Johar R, Rayburn W, Weir D, Eggert L. Birth weights in term infants. A 50-year perspective. J Reprod Med 1988; 33:813. 7. Duryea EL, Hawkins JS, McIntire DD, et al. A revised birth weight reference for the United States. Obstet Gynecol 2014; 124:16.













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58. Balsyte D, Schäffer L, Burkhardt T, et al. Sonographic prediction of macrosomia cannot be improved by combinatio combination n with pregnancy-spec pregnancy-specific ific characteristics. Ultrasound Obstet Gynecol 2009; 33:453. 59. Mazouni C, Rouzier R, Ledu R, et al. Development and internal validation of a nomogram to predict macrosomia. Ultrasound Obstet Gynecol 2007; 29:544. 60. Nahum GG, Stanislaw H. A computerized method for accurately predicting predicting fetal macrosomia up to 11 weeks before delivery. Eur J Obstet Gynecol Reprod Biol 2007; 133:148. 61. Owen P, Ogston S. Condition Conditional al centiles for the quantification of fetal growth. Ultrasound Obstet Gynecol 1998; 11:110. 62. Hedriana HL, Moore TR. A comparison of single versus multiple growth ultrasonographic ultrasonograph ic examinations in predicting birth weight. Am J Obstet Gynecol 1994; 170:1600. 63. Tarca AL, Hernandez-Andrade E, Ahn H, et al. Single and Serial Fetal Biometry to Detect Preterm and Term T erm Small- and Large-for-Gesta Large-for-Gestational-Age tional-Age Neonates: A Longitudinal Cohort Study. PLoS One 2016; 11:e0164161. 64. Bernstein IM, Catalano PM. Influence of fetal fat on the ultrasound estimation of fetal weight in diabetic mothers. Obstet Gynecol 1992; 79:561. 65. Farah N, Stuart B, Donnelly V, et al. W hat is the value of ultrasound soft tissue measurements measuremen ts in the prediction of abnormal fetal growth? J O bstet Gynaecol 2009; 29:457. 66. Landon MB, Sonek J, Foy P, et al. Sonographic measurement measurement of fetal humeral soft tissue thickness in pregnancy complicated by GDM. Diabetes 1991; 40 Suppl 2:66. 67. Sood AK, Yancey M, Richards D. Prediction of fetal macrosomia using humeral soft tissue thickness. Obstet Gynecol 1995; 85:937. 68. Mintz MC, Landon MB, Gabbe SG, et al. Shoulder soft tissue width as a predictor of macrosomia in diabetic pregnancies. Am J Perinatol 1989; 6:240. 69. Petrikovsky BM, Oleschuk C, Lesser M, et al. Predictio Prediction n of fetal f etal macrosomia using sonographically measured abdominal subcutaneous tissue thickness. J Clin Ultrasound 1997; 25:378. 70. Rigano S, Ferrazzi E, Radaelli T, et al. Sonographic measurements of subcutaneous











80. Rossi AC, Vimercati A, Greco P, et al. [Echographic measurement of subcutaneous adipose tissue as fetal growth index]. Acta Biomed Ateneo Parmense 2000; 71 Suppl 1:379. 81. Maruotti GM, Saccone G, Martinelli P. Third trimester ultrasound soft-tissue measurements measuremen ts accurately predicts macrosomia. J Matern Fetal Neonatal Med 2016; :1. 82. Cromi A, Ghezzi F, Di Naro E, et al. Large cross-sectional area of the umbilical cord as a predictor of fetal f etal macrosomia. Ultrasound Obstet Obstet Gynecol 2007; 30:861. 83. Hackmon R, Bornstein E, Ferber A, et al. Combined analysis with amniotic fluid index and estimated fetal weight for prediction of severe macrosomia at birth. Am J Obstet Gynecol 2007; 196:333.e1. 84. Matsumoto M, Yanagihara T, Hata T. Three-dimensi T hree-dimensional onal qualitative sonographic evaluation of fetal soft tissue. Hum Reprod 2000; 15:2438. 85. Lee W, Comstock CH, Kirk JS, et al. Birthweight prediction by three-dimensional three-dimensional ultrasonographic ultrasonograph ic volumes of the f etal thigh and abdomen. J Ultrasound Med 1997; 16:799. 86. Liang RI, Chang FM, Yao BL, et al. Predicting birth weight by fetal upper-arm volume with use of three-dimensi three-dimensional onal ultrasonography. ultrasonography. Am J Obstet Gynecol 1997; 177:632. 87. Song TB, Moore TR, Lee JI, et al. Fetal weight prediction by thigh volume measurementt with three-dimensional ultrasonography. measuremen ultrasonography. Obstet Gynecol 2000; 96:157. 88. Gibson KS, Stetzer B, Catalano PM, Myers SA. Comparison of 2- and 3-Dimensional Sonography for Estimation of Birth Weight and Neonatal Adiposity in the Setting of Suspected Fetal Macrosomia. J Ultrasound Med 2016; 35:1123. 89. Schild RL, Fimmers R, Hansmann M. [Can 3D volumetric analysis of the fetal upper arm and thigh t high improve conventional 2D weight estimates?]. Ultraschall Med 1999; 20:31. 90. Schild RL, Fimmers R, Hansmann M. Fetal weight estimation by three-dimensional ultrasound. Ultrasound Obstet Gynecol 2000; 16:445. 91. Farmer RM, Medearis AL, Hirata GI, Platt LD. The use of a neural network for the ultrasonographic ultrasonograph ic estimation of fetal weight in the macrosomic fetus. Am J Obstet Gynecol 1992; 166:1467. 92. Chuang L, Hwang JY, Chang CH, et al. Ultrasound estimation of fetal weight with the











103. 103. Duncan KR. Fetal and placental volumetric and functional analysis using echoplanar imaging. Top Magn Reson Imaging 2001; 12:52. 104. 104. Malin GL, Bugg GJ, Takwoingi Y, et al. Antenatal magnetic resonance imaging versus ultrasound for predicting neonatal macrosomia: a systematic review and metaanalysis. BJOG 2016; 123:77. 105. 105. Ogata ES, Sabbagha R, Metzger BE, et al. Serial ultrasonography to assess evolving fetal macrosomia. Studies in 23 pregnant diabetic women. JAMA 1980; 243:2405. 106. 106. Bracero LA, Baxi LV, Rey HR, Yeh MN. Use of ultrasound in antenatal diagnosis of large-for-gestational large-for-gestational age infants in diabetic gravid patients. Am J Obstet Gynecol 1985; 152:43. 107. 107. McFarland MB, Trylovich CG, Langer O. Anthropome Anthropometric tric differences in macrosomic infants of diabetic and nondiabetic mothers. J Matern Fetal Med 1998; 7:292. 108. 108. Durnwald C, Huston-Presley L, Amini S, Catalano P. Evaluation of body composition of large-for-gestational-age large-for-gestational-age infants of women with gestational diabetes mellitus compared with women with normal glucose tolerance levels. Am J Obstet Gynecol 2004; 191:804. 109. 109. Cohen BF, Penning S, Ansley D, et al. The incidence and severity of shoulder dystocia correlates with a sonographic measurement of asymmetry in patients with diabetes. Am J Perinatol 1999; 16:197. 110. 110. Bochner CJ, Medearis AL, Williams J 3rd, et al. Early third-trimester ultrasound screening in gestational diabetes to determine the risk of macrosomia and labor dystocia at term. Am J Obstet Gynecol 1987; 157:703. 157:703. 111. 111. Elliott JP, Garite TJ, Freeman RK, et al. Ultrasonic prediction prediction of fetal macrosomia in diabetic patients. Obstet Gynecol 1982; 60:159. 112. 112. Bethune M, Bell R. Evaluation of the measurement of the fetal fat layer, interventricular septum and abdominal circumference percentile in the prediction of macrosomia in pregnancies affected by gestational diabetes. Ultrasound Obstet Gynecol 2003; 22:586. 113. 113. Pedersen JF, Mølsted-Pedersen L. Sonographic estimation of fetal weight in













123. Fifth International Workshop-Conference on Gestational Diabetes. November, 2005. Chicago, IL. 124. 124. Luterkort M, Polberger S, Weldner BM, et al. Growth in breech presentation. presentation. Ultrasound and post-partal assessment of growth in 225 fetuses presenting by the breech in the 33rd gestational week. Acta Obstet Gynecol Scand 1986; 65:157. 125. 125. Lynch L, Lapinski R, Alvarez M, Lockwood CJ. Accuracy of ultrasound estimation of fetal weight in multiple pregnancies. Ultrasound Obstet Gynecol 1995; 6:349. 126. 126. Crowther CA, Hiller JE, Moss JR, et al. Effect of treatment of gestational diabetes mellitus on pregnancy outcomes. N Engl J Med 2005; 352:2477. 127. 127. Landon MB, Spong CY, Thom E, et al. A multicenter, randomized randomized trial of treatment for mild gestational diabetes. N Engl J Med 2009; 361:1339. 128. 128. Langer O, Conway DL. Level of glycemia and perinatal outcome in pregestational diabetes. diabetes. J Matern Fetal Med 2000; 9:35. 129. 129. Cyganek K, Skupien J, Katra B, et al. Risk of macrosomia remains remains glucosedependent in a cohort of women with pregestational type 1 diabetes and good glycemic control. Endocrine 2017; 55:447. 130. 130. Thorsell M, Kaijser M, Almström H, Andolf E. Large fetal size in early pregnancy associated with macrosomia. Ultrasound Obstet Gynecol 2010; 35:390. Topic 4443 Version 20.0











36

2117

2270

2797

3380

3594

37

2353

2500

3025

3612

3818

38

2564

2706

3219

3799

3995

39

2737

2877

3374

3941

4125

40

2863

3005

3499

4057

4232

41

2934

3082

3600

4167

4340

42

2941

3099

3686

4290

4474

Table constructed using United States National Center for Health Statistics data from 2011 for live-born singleton neonates between 500 and 6000 grams without malformations. Gestational age was based on the obstetric estimate of gestational age included in the revised 2003 United States birth certificate, which, when available, incorporates ultrasound











for weight >4000 g

71

92

55

96

for weight >4500 g

22 to 44

99

30 to 44

97 to 99

86

95

-

-

70

96

Less than 50

-

6. BPD and AC and FL adjusted by maternal characteristics characterist ics 7. Abdominal wall thickness >11 mm











6.

Pinette MG, Pan Y, Pinette SG, et al. Estimation of fetal weight: mean value from multiple formulas. J Ultrasound Med 1999; 18:813.

7.

Benacerraf BE, Gelman R, Frigoletto FD. Sonographically estimated fetal weights: accuracy and limitation. Am J Obstet Gynecol 1988; 159:1118.

8.

Sokol RJ, Chik L, Dombrowski MP, Zador IE. Correctly identifying the macrosomic fetus: improving ultrasonography-based prediction. Am J Obstet Gynecol 2 000; 182:1489.

9.

Hirata GI, Medearis AL, Horenstein J, et al. Ultrasonographic estimation of fetal weight in the clinically macrosomic fetus. Am J Obstet Gynecol 1990; 162:238.

10. Owen P, Ogston S. Conditional centiles for the quantification of fetal growth. Ultrasound Obstet Gynecol 1998; 11:110. 11. Shields LE, Huff RW, Jackson GM, et al. Fetal growth: a comparison of growth curves with mathematical modeling. J Ultrasound Med 1993; 12:271. 12. Crane JP, Kopta MM, Welt SI, Sauvage JP. Abnormal fetal growth patterns. Ultrasonic diagnosis and management. Obstet Gynecol 1977; 50:205.























Jacques S Abramowicz, MD, FACOG, FAIUMConsultant/Advi FAIUMConsultant/Advisory sory Boards: Philips Healthcare [Ultrasound (Ultrasound equipment)]. equipment)].Jennifer T Ahn, MD, FACOGNothing FACOGNothing to discloseDeborah discloseDeborah Levine, MD MDNothing Nothing to discloseVanessa discloseVanessa A Barss, MD, FACOGNothing FACOGNothing to disclose Contributor disclosures are reviewed reviewed for conflicts of interest by the editorial group. When found, these are addressed by vetting through a multi-level review process, and through requirements for references to be provided to support s upport the content. Appropriately referenced referenced content is required of all authors and must conform to UpToDate standards of evidence.

Fetal Macrosomia Uptodate

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