eMedicine Specialties > Obstetrics and Gynecology > General Obstetrics

Estimation of Fetal Weight

Author: Gerard G Nahum, MD, FACOG, FACS, Adjunct Associate Professor of Obstetrics and Gynecology, Uniformed Services University of the Health Sciences; Director of Medical Affairs, Women's Healthcare, Bayer HealthCare Pharmaceuticals
Contributor Information and Disclosures

Updated: Aug 21, 2007

Importance of Antenatal Fetal Weight Estimation

Both low birth weight and excessive fetal weight at delivery are associated with an increased risk of newborn complications during labor and the puerperium. The perinatal complications associated with low birth weight are attributable to preterm delivery, intrauterine growth restriction (IUGR), or both. For macrosomic fetuses (see Media file 1), potential complications associated with delivery include shoulder dystocia, brachial plexus injuries, bony injuries, and intrapartum asphyxia. Additional maternal risks associated with the delivery of a macrosomic fetus include birth canal and pelvic floor injuries and postpartum hemorrhage (see Table 1).

Limiting the potential complications associated with the birth of both small and excessively large fetuses requires an accurate estimation of fetal weight before delivery. This article reviews the factors that influence fetal growth and the methods that can be used to accurately estimate fetal weight.

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Standard Fetal Growth Curves

Mean birth weight can be described as a function of gestational age. Several reports subdivide such results into those that apply to women of different races, to male versus female fetuses, and to primiparous versus multiparous status. Some have further stratified the data, creating specific curves and tables for women of different heights and weights.

Standard fetal growth curves are useful for estimating the range of expected fetal weights at any particular gestational age. However, for the growth curves to be useful, the gestational age of the fetus must be properly established. Without adequate gestational dating, the data on standard fetal-growth curves cannot be interpreted successfully.

The principal limitations of standard fetal-growth curves that are derived from population-based studies are the following: (1) They apply only to fetuses that are of normal size for their gestational age and not to those with clinically significant (and potentially pathologic) growth abnormalities. (2) The data from which they are derived are highly population dependent. (3) The standard deviation (SD) associated with the estimated mean birth weight for any particular gestational age is wide, typically exceeding 450-500 g. (4) The 95% confidence interval (CI) for fetal-weight estimates are >1600 g at term (ie, ±800 g [±1 lb 12 oz], or ±23%). (5) The gestational age of the fetus must be known with a high degree of accuracy to reliably use the growth curves.

In general, standard fetal-growth curves can be expected to apply to large populations of pregnant women who have well-dated pregnancies, but the limits of their predictive accuracy make them less-than-ideal tools for estimating fetal weight in individual patients. In addition, fetal-growth curves are the most inaccurate at the extremes of fetal weight, which are the most clinically relevant situations in which they are used (eg, in fetuses that are either growth restricted or macrosomic).

What is the Normal Range for Human Birth Weight?

Deviations in fetal weight

The diagnosis of clinically significant deviations in fetal weight is based on the presupposition that the reference range for fetal weight at each gestational age is established. Before a reference range for a human birth weight can be properly determined, the gestational age of the pregnancy must first be defined because fetal weight increases rapidly after the second trimester of pregnancy.

Variations in fetal weight

The normal gestational age for the spontaneous delivery of human pregnancies is well accepted as 280 days (40 wks) from the first day of the last normal menstrual period (266 d after ovulation). Because fewer than 3% of births occur at precisely 40 weeks' gestation and because the SD for term pregnancies is 1 week, the normal range of term birth weight is typically referenced to the mean birth weight for pregnancies delivered at 38-42 weeks' gestation (ie, mean term gestational age ±2 SDs). During this 4-week interval, the typical fetus gains approximately 12.7 ± 1.4 g/day, with a difference of ±0.3 g/day depending on the sex of the fetus. (Male fetuses gain weight more rapidly than female fetuses.) The average birth weight during this period varies substantially and depends on many factors, including maternal race, size, parity, pregnancy weight gain, glucose tolerance, hematocrit, and ambient elevation.

In the United States, a study of 56,728 singleton births from 1975-1992 showed that the mean birth weight at 38-42 completed weeks' gestation was 3060-3520 g (range, 460 g [1 lb]). In Great Britain, a similar study of 41,718 newborns showed that the average was 3201-3753 g (range, 551 g [1 lb 3 oz]). In Singapore, a study of 11,026 neonates showed that the average was 2880-3290 g (range, 410 g [14 oz]).

Because birth-weight data from population studies are often nonnormally distributed, the median birth weight at each gestational age is reported. In Canada, for live births recorded in 1986-1988, the median term birth weight at 38-42 weeks' gestation for 557,359 male singleton births was 3290-3800 g (range, 510 g [1 lb 2 oz]). In the United States, for 38,818 term male births in 1984-1991, the median birth weight was 3020-3572 g (range, 552 g [1 lb 3 oz]). In Sweden, for 32,087 term male births in 1956-1957, the median birth weight was 3300-3790 g (range, 490 g [1 lb 1 oz]).

Birth weights of women from different racial groups

Median term birth weights of neonates born to women from different racial groups differ substantially. Median birth weights were compared in 17,347 newborns of Caucasian and African American women of low socioeconomic status in the United States from 1959-1966. At 40 weeks' gestation, live-born Caucasian male singleton fetuses had a median weight of 3350 g compared with 3210 g for African American male neonates (difference of 140 g). A similar difference in median birth weight was also evident among female offspring. Caucasian female newborns at 40 weeks' gestation had a median birth weight of 3210 g, and African American female neonates had a median birth weight of 3100 g (difference of 110 g).

Best method to determine the reference range for term birth weight

Perhaps the best method for defining the reference range of term birth weight is to examine fetal weights at the 2 extremes of the range (ie, below the 5th-10th percentile and above the 90th-95th percentile). In the United States, a comprehensive study of 3,134,879 live births in 1991 showed that, at 38-42 weeks' gestation, the 5th percentile of birth weight was 2543-2764 g, the 10th percentile was 2714-2935 g, the 90th percentile was 3867-4098 g, and the 95th percentile was 4027-4213 g.

Several studies from the last half of the 20th century demonstrated consistent results, showing that the 10th percentile of birth weight over the range of gestational ages listed above was 2430-3152 g, whereas the 90th percentile was 3600-4360 g. The most consistent feature of all these studies was the wide range of birth weights in the 5th-95th percentile. This range is equivalent to defining the empirical 90% CI for normal birth weight and, in the case of the most recent large-scale American study from 1991, this range is >1400 g (3 lb 1 oz). By using an 80% CI as an alternate measure, this range narrows to approximately 1100 g (2 lb 7 oz). These findings suggest that the reference range of birth weight at term might be defined as 3450 ± 700 g (2750-4150 g, or 6 lb 1 oz to 9 lb 2 oz). Table 2 shows specific birth weights associated with the different percentile ranks from 11 large studies.

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^* Ultrasonographically dated.

Perhaps the best method for establishing the reference range of term birth weight is to define the point at which newborns begin to substantially vary from the mean with respect to their prevalence of perinatal complications and perinatal death. Even within neonatal groupings that are well matched for gestational age, poor perinatal outcomes occur most frequently in fetuses who are born with weights at the extreme ends of the range (ie, <10th percentile and >90th percentile for each gestational age). By using this approach to establish a criterion, the reference range of term birth weight can be defined somewhat narrowly as about 3250-4250, or 3750 ± 500 g (7 lb 3 oz to 9 lb 6 oz).

Data from a British cohort study of 3599 neonates born in 1946 suggested that increasing term birth weight is positively correlated with cognitive ability in later life. This result persisted even after neonates of low birth weight (<2500 g) were excluded from analysis, so that all of the remaining neonates weighed 2500-5000 g.

Definitions of Deviations in Fetal Growth

Categories of fetal weight

Fetal weight may be characterized as falling into 1 of 3 categories: (1) reference range (generally defined as the 10th-90th percentile for gestational age), (2) small for gestational age (<10th percentile), or (3) large for gestational age (>90th percentile).

Until a fetus is delivered, only methods that help in evaluating fetal size in utero are of any value in assigning the fetus to these categories. Depending on the patient population that was evaluated to establish the percentiles, the standards may be misleading if they are applied to other sets of pregnant women. For instance, if standard birth-weight curves for Caucasian women are inappropriately applied to African American women, the proportion of newborns who appear to have birth weights below the 10th percentile is higher in African American neonates than in an appropriately matched group of Caucasian neonates.

Complications

Various authors in different eras have used the term low birth weight to refer to different ranges of fetal weight. Although excessive neonatal morbidity and mortality was once associated with newborns weighing 2000-2500 g, advances in neonatal care during the last quarter century have improved adverse neonatal outcomes attributable to low birth weight.

One modern classification scheme for underweight newborns is based on fetal weight alone. By using this schema, newborns can be categorized by weight to assess their risk for neonatal complications, as follows: (1) low birth weight (1501-2500 g), (2) very low birth weight (1001-1500 g), or (3) extremely low birth weight (500-1000 g).

Subclassifications in these weight groups are possible according to the incidence of neonatal morbidity and mortality in each group and the gestational age of the newborns (especially those with very low or extremely low birth weight). Successfully and accurately classifying fetuses in each of these three broad categories before delivery can help in predicting and possibly avoiding neonatal complications in underweight newborns.

Fetal macrosomia

The term fetal macrosomia denotes a fetus that is too large (see Media file 1). In ideal usage, this designation should be referenced to the mean fetal and maternal dimensions in a given population; however, it has been arbitrarily and variously defined as a birth weight >4000 g (8 lb 13 oz), >4100 g (9 lb), >4500 g, or >4536 g (10 lb) for all pregnant women, depending on the author and era. When fetal macrosomia is considered a birth weight of >4000 g, it affects 2-15% of all pregnant women, depending on the racial, ethnic, and socioeconomic composition of the population under study.

What we would like to know before delivery

Two issues concerning the size of a fetus before delivery are of interest to clinicians: the absolute size and relative size of the fetus.

The first issue is absolute fetal size (ie, actual fetal dimensions and/or fetal weight). This information is important in estimating the risk of perinatal morbidity and mortality, but it is difficult to accurately assess before delivery.

The second is the relative size of the fetus (relative fetal dimensions and/or fetal weight compared with data from some reference group). This is important to assess whether there is either IUGR or fetal macrosomia (both of which are independent predictors of perinatal morbidity and mortality). These determinations are difficult to accurately perform before delivery and depend on accurate estimations of absolute size and/or weight. These measures are difficult because they depend on choosing an appropriate reference group for comparison.

Factors Contributing to Differences in Fetal Weight

Many factors, both endogenous and extrinsic, can influence fetal weight. These encompass maternal factors (eg, race, stature, genetics), paternal factors (eg, paternal height), environmental influences (eg, altitude, availability of adequate nutrition), physiologic factors (eg, altered glucose metabolism, hemoglobin concentration, microvascular integrity), pathologic factors (eg, hypertension, uterine malformations), and complications of pregnancy (eg, gestational diabetes mellitus, preeclampsia).

Gestational Age at Delivery

Gestational age at delivery is the most significant determinant of newborn weight. Preterm delivery is the leading cause of low birth weight newborns in the United States. Other potential causes for low birth weight can collectively be attributed to IUGR (previously termed intrauterine growth retardation). Causes of IUGR include intrauterine infections, congenital syndromes, genetic abnormalities, and chronic uteroplacental insufficiency. In the case of postdate gestations, the rate of fetal macrosomia is 17-29%, as compared with 2-15% for the general population delivering term pregnancies.

The rate of fetal macrosomia increases steadily with advancing gestational age beyond 37 weeks of pregnancy (see Table 3). Consistent with this observation, 99% of fetuses that weigh >4000 g are delivered at >37 weeks' gestation.

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Maternal Race

A systematic difference is observed in the mean birth weight of babies born to mothers of different races and ethnicities. Depending on the mother's race, mean birth weights differ by as much as 141-395 g at term. Although some of this difference may be attributed to systematic differences in the mean gestational age of fetuses at delivery, to systematic racial differences in maternal characteristics (eg, maternal height and weight), and to differences in the prevalence of various diseases and complications of pregnancy that occur in different populations, an additional disparity in birth weight is attributable to racial differences per se. The precise cause of this effect is unknown, but it may be related to genetic or metabolic differences in fetal-growth potential for women of different races. Because of this effect, properly characterizing the race of mothers is important to accurately predict birth weights.

As an example, African American and Asian women have fetuses that are smaller than those of Caucasian women when appropriately matched for gestational age. If a single birth-weight standard is used, Caucasian pregnant women have a significantly higher prevalence of fetal macrosomia compared with that of African American and Asian pregnant women, and women from these latter groups have a significantly higher prevalence of small-for-gestational-age newborns compared with that of Caucasian women.

Other Parental, Environmental, and Pregnancy-Specific Determinants

After gestational age and maternal race, major parental, environmental, and pregnancy-specific determinants of birth weight are relevant for mothers with otherwise uncomplicated pregnancies (see Table 4). These include the following: (1) maternal height, (2) maternal obesity, (3) maternal pregnancy weight gain, (4) parity, (5) fetal sex, (6) ambient altitude, (7) maternal hemoglobin concentration, (8) paternal height, (9) cigarette smoking, and (10) glucose tolerance.

Taken together, these measurable factors can explain more than two fifths of the variance in term birth weight. In addition, several other major environmental factors can adversely affect fetal weight. Malnutrition is chief among these. In third-world countries where poverty among reproductive-aged women is prevalent, malnutrition a common factor can substantially affect on the size of neonates at all gestational ages.

Table 4. Routinely Measurable Parental and Pregnancy-Specific Demographic Factors that Influence Fetal Weight

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^* Ranges represent findings from 5 peer-reviewed studies. All first-order correlations with term birth weight were statistically significant at the P <.05 level, except for the 1-h 50-g glucose result. Patients with diabetes were excluded from all analyses.

Maternal height

Maternal height is an easily measurable physical characteristic that is positively correlated with term fetal weight. Although lifestyle choices can potentially modify other maternal physical features (eg, maternal weight and BMI), maternal height is arguably the single best measure of native human-size potential.

Barring special circumstances (eg, malnutrition in childhood, scoliosis, intrinsic bone disease) adult height is a trait that has genetic underpinnings that are generationally transmissible. Family pedigree studies have shown that, on average, "big people have big babies and small people have small ones." One would be intuitively challenged to argue with this line of reasoning, and data from numerous studies have independently confirmed the direct relationship of maternal height to the birth weight of offspring.

Maternal obesity

The level of maternal obesity independently influences fetal weight such that the more a mother weighs, the larger her fetus is likely to be. This occurs because maternal weight and fetal weight are directly related, and women with high BMIs are at increased risk for developing diabetes during pregnancy (see Diabetes Mellitus below).

Maternal pregnancy weight gain

Maternal pregnancy weight gain is important with regard to fetal growth, such that the greater the weight gain is, the larger the fetus is likely to be. Weight gain during pregnancy is generally proportional to the caloric intake of a mother and, the greater the number of calories consumed, the more is available for incorporation into the developing tissues of the fetus. In addition, increased pregnancy weight gain is associated with an increased risk of developing gestational diabetes (see Diabetes Mellitus below).

Parity

Parity is directly and independently associated with fetal size. The greater the maternal parity, the larger the fetus is likely to be. Maternal parity is closely linked to maternal age, but once maternal parity is specified, maternal age is not an independent predictor of fetal weight. At term, a fetus typically gains 0.2-0.5 g/day for each increase of 1 in maternal parity.

Fetal sex

Fetal sex is associated significantly with birth weight and independently accounts for approximately 2% of the variance. Female fetuses are smaller than male fetuses when matched for gestational age and for all other known factors that influence fetal weight. On average, male fetuses weigh more than females by 136 g (5 oz) at term.

Ambient altitude

Ambient altitude predictably influences fetal weight such that, when controlled for all other variables, an increase in altitude of 1000 m accounts for a reduction in term birth weight of 102-145 g. In addition, adult hemoglobin concentrations increase by 1.52 g/dL for every 1000-m increase in ambient altitude. Numerous studies have demonstrated the dependence of fetal weight on ambient altitude. This effect is independent of all other factors that can influence fetal weight. The magnitude of the effect of altitude on fetal weight is -30 to -43 g per 1000 feet above sea level at term.

Several potential explanations have been proposed for the inverse relationship between increasing altitude and fetal weight; they include (1) the decrease in oxygen tension with increasing altitude, (2) the increase in maternal hemoglobin concentration with increasing altitude, and/or (3) the decrease in maternal plasma volume with increasing altitude.

Maternal hemoglobin concentration

Maternal hemoglobin concentration at constant altitude independently explains 2.6% of the variance in birth weight, apart from all other known predictive variables. The relationship between birth weight and circulating maternal hemoglobin concentration is inverse, such that for each 1.0-g/dL increase in maternal hemoglobin concentration, term birth weight is reduced by 89 g (see Media file 2).

This effect may be as the result of changes in blood viscosity. Blood is a highly non-Newtonian fluid that has a rapid nonlinear rise in viscosity with increasing hematocrit. Increasing viscosity tends to retard the rate of blood flow through small vessels, including those in the placental bed, raising extraction ratios and lowering solute gradients. This effect may partly explain why increasing altitude (which increases circulating hematocrit and hemoglobin concentrations) results in progressively lower mean birth weights.

Paternal height

Paternal height independently accounts for 2% of the variance in birth weight (10 g/cm of fetal weight at term). Offspring of fathers with heights 2 SDs above or below the mean have a term birth weight that is increased or decreased by 125 g, respectively. Normal variability in paternal height explains an independent portion of the variance in term birth weight of up to 250 g that other maternal, environmental, or pregnancy-specific factors do not account for. Paternal weight and BMI, which are acquired traits and which depend on lifestyle choices and behaviors, do not independently influence fetal weight. Paternal age also has no effect on birth weight up to at least the age of 60 years.

Cigarette smoking

Cigarette smoking during pregnancy both increases maternal hemoglobin concentrations and systematically lowers term birth weight by 12-18 g per cigarette smoked per day. That is, a mother who smokes 1 pack per day will likely have a baby with a mean birth weight reduction of 240-360 g at term.

Diabetes Mellitus

Uncontrolled maternal diabetes mellitus is commonly associated with excessive fetal weight. Glucose is the primary substrate fetuses require for growth. When maternal glucose levels are excessive, abnormally high rates of fetal growth can be expected. Compared with the baseline rate of fetal macrosomia of 2-15% in the general population (depending on the group studied), the rate among mothers with poorly controlled gestational diabetes is elevated (20-33%). Because of routine glucose screening during pregnancy and the stringent glucose criteria now used to monitor and treat women who have diabetes during pregnancy, undiagnosed and poorly controlled gestational diabetes mellitus are now unusual, and the rate of macrosomia among women with frank gestational diabetes has recently diminished.

Even in women without diabetes mellitus, elevated glucose values in pregnancy predispose their fetuses to increased birth weight. The subgroup of women at highest risk for fetal macrosomia are those who are unmonitored and untreated, who have abnormal 1-hour glucose results during pregnancy and a subsequent normal 3-hour glucose tolerance tests, and who have a single abnormal value indicative of only mild glucose intolerance.

Other Maternal Illnesses and Complications of Pregnancy

Several maternal illnesses and complications of pregnancy are associated with decreased birth weight. The most common are chronic maternal hypertension and preeclampsia. Chronic maternal hypertension is associated with a mean decrement in birth weight of 161 g at term. For mild preeclampsia, the mean reduction is at least 105 g. When severe preeclampsia or HELLP syndrome is a complication, an additional and generally less predictable downward adjustment in fetal weight must be made.

Some maternal connective-tissue diseases, intrauterine infections (eg, viral, parasitic, bacterial), chromosomal abnormalities, and congenital syndromes are also associated with small-for-gestational-age fetuses.

Diagnosis of Deviations in Fetal Weight

Techniques for estimating fetal weight

All of the currently available methods for assessing fetal weight in utero are subject to substantial predictive errors. These errors are most clinically relevant at the 2 extremes of fetal weight (eg, <2500 g, likely the product of premature deliveries, and >4000 g, at risk for the complications associated with fetal macrosomia).

Tactile assessment of fetal size

Tactile assessment of fetal size is the oldest technique for assessing fetal weight and is also referred to as clinical palpation or Leopold maneuvers. It involves manual assessment of fetal size by the obstetrical practitioner. Worldwide, this method is used extensively because it is both convenient and virtually costless; however, it is a subjective method associated with notable predictive errors.

Clinical risk factor assessment

Quantitative assessment of clinical risk factors is valuable in predicting deviations in fetal weight. Table 5 shows the odds ratio (ORs) of fetal macrosomia for 11 clinical risk factors.

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Note—Data compiled from 14 studies of the prevalence of risk factors for fetal macrosomia among women delivering fetuses weighing 4000 g or more and control subjects with birth weights of <4000 g.

^* All classes, including gestational diabetes mellitus. Wide range of values reflects differences among studies in criteria for screening and diagnosis, prevalence of disease in the populations under study, and the generally good (but variable) success of glucose control during pregnancy.

Maternal self-estimation

A third method for estimating fetal weight is maternal self-estimation. Perhaps a surprise, in some studies, self-estimates of fetal weight in multiparous women were comparably accurate to findings on clinical palpation in predicting fetal weight and abnormally large fetuses at term (see Table 6).

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Obstetric ultrasonography

The most modern method for assessing fetal weight in utero involves the use of fetal measurements obtained during obstetrical ultrasonography. The advantage of this technique is that it relies on linear and/or planar measurements of in utero fetal dimensions that are objectively definable and probably reproducible. Findings from prospective studies have shown that ultrasonographic estimates of fetal weight are no better than clinical palpation in predicting fetal weight; these observations have undermined early expectations that this method might provide an objective standard for identifying fetuses of abnormal size for gestational age (see Table 6).

Taken together, these findings suggest that the prediction of fetal weight is not an exact science and that it requires additional refinement.

Accuracy of Fetal Weight Prediction by Using Different Methods

Accuracy of clinical palpation for estimating fetal weight

One study showed that the sensitivity of clinical palpation for identifying a birth weight of <2500 g was only 17%, with an associated positive predictive value of 37%. At the upper limit of term fetal weights, 2 studies have shown that the positive predictive value of clinical palpation for predicting birth weight >4000 g was 60-63%, with an associated sensitivity of 34-54%.

Furthermore, findings from 2 studies have suggested that the accuracy of clinical palpation for predicting fetal weight does not depend on the level of training of the operator, whereas data from another study suggests that resident physicians in obstetrics and gynecology are systematically better than medical students at estimating term birth weight by using this technique (see Table 7).

The mean absolute percentage error in birth weight prediction by using clinical palpation for term fetuses at >37 weeks' gestation is 7.2-10.6% (see Table 6). For a fetus predicted to weigh >4000 g, the average error in birth-weight estimation routinely exceeds 300-400 g. In 1 study, >6% of fetal weights were wrongly assessed by >1370 g (3 lb).

Table 7. Accuracy of Clinical Palpation for Predicting Term Birth Weight by Clinician

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Accuracy of obstetric ultrasonography for estimating fetal weight

Obstetric sonographic assessment for the purpose of obtaining fetal biometric measurements to predict fetal weight has been integrated into the mainstream of obstetric practice in the past quarter century. From its inception, this method has been presumed to be more accurate than clinical methods for estimating fetal weight. The reasons for this assumption vary, but the fundamental underlying presumption is that sonographic measurements of multiple linear and planar dimensions of the fetus provide sufficient parametric information to allow for accurate algorithmic reconstruction of the 3-dimensional fetal volume of varying tissue density. Consistent with these beliefs, much effort has generated best-fit fetal biometric algorithms to make birth weight predictions based on obstetric ultrasonographic measurements. As such, the ultrasonographic technique represents the newest and most technologically sophisticated method of estimating fetal weight.

Modern algorithms that incorporate standardly defined fetal measurements (eg, some combination of fetal AC, FL, BPD, and HC) are generally comparable in their overall accuracy in predicting fetal weight. Table 8 shows a categorization of 27 ultrasonographic algorithms according to the type of fetal biometric information that they incorporate.

The formulas are arranged into 8 groups according to the type of fetal biometric information that they rely on to make their fetal weight predictions, as follows:

1. AC
2. FL
3. AC + FL
4. AC + BPD
5. AC + HC
6. AC + BPD + FL
7. AC + HC + FL
8. AC + HC + BPD + FL

When other sonographic fetal measurements are used to estimate fetal weight (eg, humeral soft-tissue thickness, ratio of subcutaneous tissue to FL, cheek-to-cheek diameter), these nonstandard measurements do not significantly improve the usefulness of obstetric ultrasonography in predicting fetal weight, except in special patient groups (eg, mothers with diabetes).

Table 8. Algorithms for Ultrasonographic Fetal Biometric Prediction Calculating Estimated Fetal Weight*

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^* BW expressed in kilograms. (For other equations, results expressed in grams).

^† The Shinozuka equation has been modified from its original published form by substituting the fetal AC measurement for the abdominal transverse and anteroposterior diameters in the original equation; Combs et al have recalculated its coefficients.

Of note is that higher-order terms appear in 16 of the 27 ultrasound prediction equations that are listed in Table 8. One group evaluated the value of the 4 standard ultrasonographic fetal biometric parameters for predicting fetal weight to determine whether their correlation with fetal weight increased with increasing order. Table 9 shows their results.

Table 9. Correlations of Ultrasonographic Fetal Measurements With Term Fetal Weight

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The predictive value of any of the standard ultrasonographic fetal biometric measurements for estimating fetal weight did not increase with increasing order. Consistent with these findings, another group using an unrelated set of patients found that the correlations of these 4 ultrasonographic measurements at first-order with fetal weight were as follows: BPD = 0.58, HC = 0.65, AC = 0.78, and FL = 0.52. Again, the correlation did not increase with increasing order.

These results suggest that the fetal AC is the single best ultrasonographic predictor of fetal weight and that the predictive value of none of the measurements increase with increasing order. The implication is that the incorporation of higher-order terms into ultrasonographic prediction algorithms is not theoretically or empirically justified.

Limiting factors associated with the ultrasonographic prediction of fetal weight are (1) imprecise imaging of fetal structures (due to limitations such as patient obesity, placentation, oligohydramnios, and/or fetal position), (2) limited number of linear and/or planar measurements that can be taken of the complex 3-dimensional fetal conformation, (3) fetal tissues of similar dimensions with varying densities (eg, bone > muscle > adipose tissue), (4) unavoidable operator- and equipment-related measurement errors and approximations, and (5) inappropriate algorithmic compounding of measurement errors and approximations by the incorporation of high-order terms.

In a study of 1034 patients, the mean absolute percentage error associated with the calculation of estimated fetal weights based on BPD, AC, and FL (according to a widely used Hadlock equation) was 10.0-11.3%, depending on the gestational age of the fetus (ie, after crude stratification of fetal size). When the mean absolute percentage error of the method is assessed for the 3 clinically significant ranges of fetal weight (<2500, 2500-4000, >4000 g), the mean absolute percentage error of the technique is typically lowest (±7.1-10.5%) for the mid and high ranges and slightly high for the low range (±8-11%).

When another commonly used measure of accuracy is used (percentage of fetuses with weight accurately estimated to within ±10% of actual birth weight), weight was accurately predicted to within these limits for 56% of fetuses weighing <2500 g, for 58% of fetuses weighing 2500-4000 g, and for 62% of fetuses weighing >4000 g.

When the accuracy of detecting clinically relevant deviations in term birth weight (<2500, >4000, and >4500 g) is sonographically assessed, the positive predictive value is 44-55%, with sensitivities of 58-71% at term. As expected, for preterm fetuses delivered at <37 weeks' gestation who have a decreased mean birth weight, the 1-way accuracy of sonographic fetal biometric classifications of clinically significant deviations (ie, low birth weight) improved. The positive predictive value of a sonographic estimate of fetal weight of <2500 g is 87% for preterm fetuses, with a sensitivity of 90%, and the positive predictive value for a sonographic estimate of fetal weight of <1500 g is 86%, with a sensitivity of 93%.

Two groups investigated the relative accuracy of the different classes of ultrasonographic fetal-biometric algorithms for predicting fetal weight. In the first study, 74 patients with normal, term, singleton pregnancies underwent complete sonographic examinations within 1.4 weeks of delivery. The mean absolute predictive accuracy of 27 algorithms ranged from ±295 g for the Warsof equation (based on fetal AC alone) to ±520 g for the Woo equation (based on both AC and BPD) (see Table 10). The accuracy of the algorithms to within ±15% of actual birth weight ranged from 54% for the Higginbottom equation (based on AC alone) to 85% for the modified Shinozuka equation (based on AC, BPD, and FL). To predict fetal weight to within ±10% of actual birth weight, accuracy ranged from 31% for the Woo equation (based on AC and BPD) to 70% for the Hadlock equation (based on AC, BPD, HC, and FL).

Thirteen (48%) of the 27 equations did not predict fetal weight to within ±15% of actual weight better than guessing the mean birth weight. For fetal-weight predictions to within ±10% of actual weight, 20 (74%) of the ultrasonographic algorithms performed better than guessing.

Seventeen (63%) of the 27 ultrasonic algorithms generated substantially lower mean absolute prediction errors and mean absolute percentage errors than guessing. For these equations, the improvement in the mean absolute prediction error and the absolute percentage prediction error was 96-154 g (3.2-5.0%) depending on the algorithm used. The 10 remaining equations resulted in estimates no better than simple guesses of 3455 g for each newborn.

Overall, the 3 algorithms that were most accurate were those of Ott et al (based on AC, HC, and FL), Shinozuka et al (based on AC, BPD, and FL, as Combs et al modified it), and Warsof et al (based on AC alone). Results in any category of analysis for these equations were not significantly different.

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^* All comparisons with actual birth weight were calculated by adding to the predicted ultrasonographic birth-weight rate of 12.4 g/day (for females) or 13.0 g/day (for males) for the time elapsed between the date of ultrasonographic fetal biometric assessment and the actual date of delivery.

†Results for the ultrasonographic prediction equation were statistically superior to those obtained by guessing the mean term birth weight at P <.05. Comparisons were made by using the Student t test for mean absolute errors and mean absolute percentage errors and by means of x2 analysis for the percentage of birth weight predictions within ±10% and ±15% of actual birth weight.

‡The Shinozuka equation has been modified from its original published form by substituting the fetal AC measurement for the abdominal transverse and anteroposterior diameters in the original equation; Combs et al have recalculated its coefficients.

Table 11. Comparison of the Most Accurate Ultrasonographic Algorithms That Incorporate Different Ultrasonographic Parameters to Predict Term Fetal Weight (n = 74)

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^* Calculations were made by adding to the predicted ultrasonographic birth weight 12.4 g/day (for females) or 13.0 g/day (for males) for the time elapsed between the date of ultrasonographic fetal biometric assessment and the actual date of delivery.

^† The Shinozuka equation has been modified from its original published form by substituting the fetal AC measurement for the abdominal transverse and anteroposterior diameters in the original equation; Combs et al have recalculated its coefficients.

When used to make predictions concerning the occurrence of fetal macrosomia, the 13 best-performing ultrasonographic equations had 25-75% sensitivity for fetal macrosomia >4000 g with a positive predictive value of 41-63% (see Table 11). The 4 most accurate algorithms that possessed superior combinations of a sensitivity of >40%, a positive predictive value of >50%, and a likelihood ratio of >5.0 for the prediction of fetal macrosomia were the equations of Ott et al, Shinozuka et al (as Combs et al modified it), Jordaan (based on AC and BPD), and Warsof et al (based on AC alone).

In a second study of 82 unrelated patients who had normal term pregnancies and who underwent complete ultrasonography within 1.2 weeks of delivery, the predictive accuracy of 25 ultrasonographic prediction equations was evaluated. Table 12 shows the results. 

Table 12. Comparison of the Accuracy of Methods for Predicting Term Birth Weight (n = 82)

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^* The Shinozuka equation has been modified from its original published form by substituting the fetal AC measurement for the abdominal transverse and anteroposterior diameters in the original equation; Combs et al have recalculated its coefficients.

^† n = 60 for ultrasonographic equations that incorporate fetal HC as a predictive variable.

When these ultrasonographic prediction results are compared with an approach that relies on only quantitative assessment of maternal and pregnancy-specific characteristics (see Predicting fetal weight by using algorithms derived from parental and pregnancy-specific characteristics), the accuracies of the algorithms are comparable (see Media file 3). Table 13 shows results for the different ultrasonographic equations compared with each other and with the maternal-characteristics approach to birth-weight prediction.

After fetal AC is incorporated into the prediction algorithm, all types of ultrasonographic equations perform essentially equivalently in estimating fetal weight, and the addition of other standard ultrasonographic parameters generally does not increase the accuracy. Furthermore, the results demonstrate that no ultrasonographic algorithm for birth-weight prediction is superior to the maternal-characteristics approach. 

Table 13. Comparison of the Absolute Accuracy of Equations and Methods for Predicting Term Birth Weight (n = 82)

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With regard to predicting the occurrence of fetal macrosomia >4000 g, Table 14 shows the results for 17 of the best-performing ultrasonographic birth-weight prediction equations in 7 categories. The overall classification accuracy of the equations was 60-80% with likelihood ratios of 1.1-4.1. By comparison, the single maternal-characteristics equation to which they were compared in head to head fashion had an overall classification accuracy of 83%, with a likelihood ratio of 5.4. 

Table 14. Direct Comparison of the Accuracy of Methods of Predicting Fetal Weight Greater Than 4000 g (n = 60)

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^* The likelihood ratio was used to compare the probability of having a positive result (ie, prediction of >4000 g) in a woman carrying a truly macrosomic fetus with the probability of having a positive result in a woman carrying a fetus with a true weight of <4000 g. The utility of the test for assisting in clinical decision making can be categorized as follows: >10, very useful; 5-10, often useful; 2-5, sometimes useful; and 1-2, not generally useful.

^† The Shinozuka equation has been modified from its original published form by substituting the fetal AC measurement for the abdominal transverse and anteroposterior diameters in the original equation; Combs et al have recalculated its coefficients.

Table 15 shows the sensitivities, specificities, positive predictive values, and negative predictive values of the sonographic technique for predicting clinically significant variations in fetal weight as a function of both fetal weight and gestational age. For any set of standard ultrasonographic input parameters (any subset of AC, FL, BPD, and/or HC), Using Ultrasound to Predict Fetal Weight can be used to estimate fetal weights by using 26 ultrasonographic fetal biometric equations, with the mean, median, and range of results. 

Table 15. Accuracy of Sonographic Fetal Biometry for Detecting Clinically Relevant Deviations in Fetal Weight

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Source—Adapted from Chauhan et al.

Table 16 shows the results of 5 studies of the accuracy of the ultrasonographic technique for predicting fetal macrosomia of >4000 g at term. On meta-analysis of data from these 5 studies of 2367 term pregnancies of >37 weeks' gestation, the positive predictive value for detecting fetal weight >4000 g with ultrasonographic fetal biometry was 59% with a sensitivity of 59%. The average predictive error in birth-weight estimates for fetuses of >4000 g with this method was routinely >300-400 g.

Table 16. Accuracy of Obstetric Ultrasonography for Predicting Fetal Macrosomia of Greater Than 4000 g at Greater Than 37 Weeks' Gestation

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The notion that multiple obstetric sonographic fetal biometric evaluations might be superior to a single examination for predicting fetal weights has been examined. In 1 study, the accuracies of birth-weight percentile predictions were statistically similar during the third trimester. In this study, which used the Shepard ultrasonographic algorithm, weight was accurately estimated to within ±10% in 38% of fetuses after a single ultrasonographic assessment of fetal dimensions, and 42% were correct to within ±10% after multiple sonographic examinations.

Table 17 shows the accuracy for predicting small- and large-for-gestational-age fetuses by using these sonographically derived estimated fetal weights, which are obtained from 1 or more sonographic examinations.

Table 17. Accuracy of Single vs Multiple Sonographic Fetal Biometric Examinations for Detecting Clinically Relevant Deviations in Fetal Weight

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^* Prevalence of small-for-gestation-age fetuses was 19 (7.2%) of 264 patients, and the prevalence of large-for-gestation-age fetuses was 46 (17.4%) of 264 patients.

Another important question is the potential difference in the predictive accuracy of fetal weight estimated by using fetal biometry performed by professional sonographers in a controlled setting compared with hospital-based resident physicians performing the studies in a labor and delivery unit. Although the interobserver variation in measurements was small, they may still introduce unacceptable variability into the parameters used to estimate for fetal weight by using fetal biometric algorithms.

In a study designed to address this clinically important question, the mean absolute percentage error associated with ultrasonographic estimates of fetal weight by staff physicians in a labor and delivery suite (±9.3%) was comparable to that reported for professional ultrasonographers in a controlled setting. Therefore, no clinically important systematic bias is introduced into such results based on differences in operator training or diagnostic setting.

Findings from several studies have challenged the overall accuracy of sonographic birth-weight estimations. Investigators from more than a dozen investigations have concluded that ultrasonography may be no more accurate for predicting birth weight than clinical palpation or even maternal self-estimation. Findings from 4 studies have also suggested that quantitative assessment of maternal characteristics may be as accurate as obstetric ultrasonography for predicting fetal macrosomia.

Accuracy of maternal self-estimations of fetal weight

Four groups of researchers examined the accuracy of self-estimations of fetal weight by parous women. The mean absolute percentage error for their predictions was 8.7-11.5% for term fetuses, with mean absolute birth weight errors of 305-402 g (see Table 6). In a small study that addressed the sensitivity for macrosomia >4000 g, it was 56% (see Table 18). These results are comparable to those reported for both clinical palpation and obstetric ultrasonography. 

Table 18. Comparison of Published Accuracy of Methods for Predicting Term Fetal Macrosomia of Greater Than 4000 g

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^† Low rate from Chauhan et al, 1992 (106 patients); high rate from Nahum 2002.

^‡ Chauhan et al, 1995 (602 patients).

^§ Prevalence of fetal macrosomia was higher in this group than for the other study groups.

Predicting fetal weight by using algorithms derived from parental and pregnancy-specific characteristics

New and theoretically defensible equations to prospectively predict individual birth weights from maternal and pregnancy-specific characteristics have been developed. The predictive efficacy of 59 scientifically justifiable terms was evaluated simultaneously to eliminate any confounding covariation and to determine predictors could account for variations in birth weight. Aside from maternal race, 7 maternal and pregnancy-specific variables were independently important in predicting birth weight for otherwise healthy pregnant women. One additional paternal factor (paternal height) was independently predictive of birth weight. Table 4 shows the first-order correlations of various predictors with fetal weight.

By using these routinely recorded variables, an equation based on maternal and pregnancy-related characteristics alone was developed to help predict birth weight based on the following factors (see Equation 1 below).

• Maternal height
• Maternal weight at 26 weeks' gestation
• Maternal weight gain rate during the third trimester
• Maternal hemoglobin concentration during the third trimester
• Parity
• Fetal sex
• Gestational age at delivery

These prospectively measurable variables account for >36% of the variance in term birth weight and can be used to accurately predict fetal weight to within ±267-288 g (±7.6-8.4% of individual birth weights). In addition, 68-75% of newborn weights can be estimated to within ±10% of the actual birth weights by using this method.

Birth weight (in grams) = = -3044 + gestational (in days) X {[23.6 + (0.243 X fetal sex)

+ (0.000281 X material height in centimeters X maternal weight at 26 wk in kilograms)

+ (3.11 X maternal weight-gain rate in kilograms per day X [parity + 1])

- (0.318 X maternal hemoglobin concentration in grams per deciliter)},

where fetal sex = +1 for male, -1 for female, or 0 for unknown, and where gestational age = days since the onset of the last normal menses, which equals the conception age (in days) + 14.

Prospective use of this maternal-characteristics equation yields a correlation of 0.59 between predicted and actual birth weights, with a mean absolute prediction error of 275 ± 229 g (8.0% ± 7.1 of actual birth weight). In 86% of cases, the birth weight predictions were accurate to within ±15%, and in 70% of cases, they were accurate to within ±10% of actual birth weight.

For these types of parental-characteristics prediction equations for estimating fetal weight, the overall findings are as follows:

• Media file 4 shows the trade-off between sensitivity and specificity for the prediction of fetal macrosomia >4000 g.
• Media file 5 shows the trade-off between the positive and negative predictive value for the prediction of birth weight >4000 g.
• Media file 6 shows the receiver operating characteristic curve depicting the overall accuracy of the equation for predicting fetal macrosomia. The area under the curve is 0.82.
• By using a cutoff value of 3775 g, the sensitivity for predicting fetal macrosomia >4000 g is 54%, the specificity is 92%, the positive predictive value is 52%, and the negative predictive value is 93%.

Which of the methods for predicting fetal weight is the most accurate?

The accuracy of the different methods for predicting fetal weight depends on the gestational age and the range of birth weights under study. Again, for this purpose, dividing fetuses into the three birth weight categories of <2500 g, 2500-4000 g, and >4000 g is useful. Table 19 shows the relative accuracy of clinical palpation versus obstetric sonographic fetal biometry for these ranges. With reference to the clinically significant birth weight ranges of <2500 g and >4000 g, the accuracy of sonographic fetal biometry appears to be superior to clinical palpation for predicting fetuses weighing <2500 g, whereas the 2 techniques appear to have comparable predictive accuracy for fetuses weighing 2500 g or more. 

Table 19. Accuracy of Clinical Palpation vs Sonographic Fetal Biometry for Predicting Birth Weight

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A group directly comparing the 4 methods of fetal-weight prediction in normal term pregnancies found no difference between the accuracy of the clinical methods (eg, clinical palpation, use of parental-characteristics prediction equations, and maternal self-estimation) and ultrasonographic fetal biometry. Eight representative ultrasonographic algorithms were assessed for this purpose. The mean birth weight for newborns was 3445 ± 458 g, with a range of 2485-4790 g.

Table 20 summarizes the results.

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Ten other studies have been performed to directly compare the accuracy of clinical palpation to ultrasonographic fetal biometry in the same group of pregnant women, and 4 more that were performed compared clinical palpation to self-estimates of fetal weight after 37 weeks' gestation. Two studies have also been conducted to compare clinical palpation to ultrasonographic fetal biometry and self-estimations of fetal weight (see Table 6). All of the methods have significant predictive errors in fetal-weight estimations for term fetuses in the range of 288-560 g, and no consistent or clear superiority of ultrasonographic fetal biometry over the other techniques was found.

The most accurate method of birth-weight prediction

Equations to predict fetal weight based on maternal characteristics alone can be successfully applied to new sets of pregnant women with absolute prediction accuracies of ±275-288 g (±8.0-8.4%) at term. Ultrasonographic prediction equations, which depend exclusively on fetal biometric information, have absolute prediction accuracies of ±263-646 g (±7.5-18.8%) at term. In head-to-head comparisons, sonographic techniques to predict birth weight in term patients were no more accurate than methods that depend exclusively on the quantitative analysis of parental and pregnancy-specific characteristics (see Table 12, Table 13, Table 14, Table 18, Table 20, and Media file 3).

By combining the information from ultrasonographic fetal biometry with that from the quantitative analysis of parental and pregnancy-specific characteristics, it is possible to derive combination prediction algorithms to optimize the accuracy of fetal-weight estimations. Both types of information can produce approximately equivalent accuracies in predicting birth weight and fetal macrosomia. Because the data are fundamentally different, their combination is synergistic and improves the results of either technique alone for estimating fetal weight before delivery.

A set of 61 unique prediction algorithms was developed with selection logic for maternal races and combinations of available ultrasonographic, laboratory, and parental data. All of the information needed for their use is routinely available from standard prenatal patient charts, and ultrasonographic fetal biometric information can be collected up to 11 weeks before delivery.

The combination prediction algorithms can be categorized into 4 groups. They require different parental characteristics information, and they incorporate additional fetal biometric information of 1 of the following types:

• Ultrasonographic AC measurement within 11 weeks of delivery
• Ultrasonographic HC measurement within 11 weeks of delivery, but without an AC measurement available
• Ultrasonographic FL measurement within 11 weeks of delivery, but without either an AC or HC measurement available
• Ultrasonographic BPD measurement within 11 weeks of delivery, but without an AC, HC, or FL measurement available

Because the optimal prediction algorithm depends on the availability of information, the combination method can be implemented as a computer program that automatically chooses the proper algorithm for the patient's specific information and the ultrasonographic fetal biometric data available. One tool to estimate fetal weight and/or the risk of fetal macrosomia as a function of gestational age is available at Baby Weight Finder. Ultrasonographic information is not required to obtain results, but, if available, it can be inputted to supplement the parental and pregnancy-specific information.

Birth weight in grams = -1627 + (13.18 X fetal AC) + (16.23 x delta) + [0.00009966 X gestational age in days X maternal height in centimeters X maternal weight at 26 wks in kilograms] + [3.173 X gestational age in days X maternal weight-gain rate in kilograms per day) X (PARITY + 1)],

where delta = elapsed time in days between the acquisition of ultrasonographic fetal biometric measurements and the delivery date, and gestational age = days since the onset of the last normal menses, which equals the conception age (days) + 14.

By adding ultrasonographic fetal biometric parameters to different types of parental characteristics equations, 78% of the variance in term birth weight can be explained, and the predictive accuracy is better than ±6.0% (±213 g). These fetal-weight estimates are superior to what can be obtained by using either parental characteristics or ultrasonographic fetal biometry alone and can be made up to 11 weeks before delivery.

In addition, by using this combined method, up to 90% of newborns can be properly classified as normal weight or macrosomic. The sensitivity for fetal macrosomia >4000 g can be increased to 83%, with an associated positive predictive value of 65% and a negative predictive value of 95%. The risk of fetal macrosomia as a function of gestational age can then be expressed as a simple percentage (1-99%), and individualized patient risk assessments can be made long in advance of delivery. Furthermore, if ultrasonographic fetal biometric data are not available, the system can be used as a tool to screen for patients who should undergo ultrasonography to make fetal weight estimates optimally reliable.

Diagnosing Significant Deviations in Fetal Weight and Management Options

Diagnosis and Management

Developing a consensus of indicators

All techniques for estimating fetal weight have significant degrees of inaccuracy. Therefore, a reasonable strategy for estimating fetal weight is to use several estimates based on different sources of clinical and ultrasonographic information. If this strategy is applied, the following practical and semiquantitative schema for making an antenatal diagnosis of fetal weight in the clinical setting can be suggested:

• Assess maternal risk factors for predispositions to deviations in fetal growth at the initial prenatal visit and at the start of the third trimester. Any gravida who has 1 or more of the following conditions should be considered at high risk for abnormal fetal growth and should undergo further assessment with other techniques to estimate the fetal weight:
  • Poorly controlled diabetes mellitus (any class, including gestational diabetes)
  • Abnormal 1-hour glucose screening test result (>135 mg/dL)
  • Single abnormal value on 3-hour oral glucose tolerance testing
  • Obesity
  • Abnormally tall or short stature
  • Excessive or inadequate pregnancy weight gain
  • High parity
  • Preterm gestation
  • Postdate pregnancy
  • Chronic hypertension
  • Preeclampsia (including pregnancy-induced hypertension and hemolysis, elevated liver enzyme levels, and low platelet count [HELLP syndrome])
  • Microvascular disease
  • Cigarette smoking
  • Residence at high altitude
• After a gravida is thought to be at risk for either excessive fetal growth or IUGR, use all applicable modalities to determine which method (if any) might suggest that the fetus has a weight outside of the reference range for its gestational age.
  • Standard fetal weight for comparison can be obtained from the 50th percentile of published fetal-growth curves derived from patient populations that are well matched to the particular patient under consideration.
  • Clinical palpation and ultrasonographic fetal biometry can be used to estimate fetal size regardless of gestational age.
  • Prediction equations based on parental characteristics can be used to estimate the fetal weight in healthy pregnant women of all races at or near term.
  • If results of any 2 modalities suggest that the fetal weight is abnormal for gestational age (ie, > 2 SDs from the expected mean or 50th percentile), presume that the fetus is growing at an abnormal rate.
  • If so, consider obtaining a more reliable estimate of fetal weight by using a combination prediction algorithm that integrates parental characteristics with pregnancy-specific and ultrasonographic fetal biometric information. One such tool is available at Baby Weight Finder.
  • Order serial assessments of fetal growth to determine the velocity of ongoing fetal weight gain.
  • If both fetal weight for gestational age and the velocity of fetal weight gain are abnormal, the evidence for a clinically significant abnormality in fetal growth becomes more compelling than before. Manage the pregnancy accordingly, with the presumption that the fetal size is outside the reference range of expected values.

Option for suppression of labor in women carrying undersized fetuses

In general, the case can be made to attempt labor suppression in women carrying preterm fetuses weighing <2000-2500 g. As stressed previously, most cases of low birth weight are associated with preterm gestations. However, any recommendation in this circumstance regarding tocolysis presupposes the following: (1) that no immediate fetal or maternal indications mitigate the timely delivery of the undersized fetus and (2) that the undersized fetus will continue to grow along an acceptable growth curve if the gestation is allowed to continue. In many cases, both of these assumptions are invalid. For instance, many women who deliver preterm neonates are allowed to do so because of compelling fetal or maternal medical conditions that warrant timely delivery (eg, intrauterine infection, severe uteroplacental insufficiency, or severe preeclampsia). If fetal infection or IUGR is present, the preterm delivery of an underweight fetus may be indicated.

In these circumstances, the increased risk of morbidity and mortality to both the fetus and mother by allowing the pregnancy to continue may outweigh the increased risk of perinatal complications associated with the delivery of an underweight fetus. In addition, in some circumstances, the inadequate velocity of fetal growth might mandate a decision for delivery. In such cases, the presumption is that extrauterine growth and development in the neonatal nursery would be superior to that achieved in utero. Clinical judgment is of paramount importance in deciding when to affect delivery and when to attempt labor suppression. Detailed considerations in this decision are beyond the scope of this article.

Option for labor induction in women carrying oversized fetuses

In fetuses delivered before 37 weeks' gestation, fetal macrosomia is a rarity; >99% of macrosomic fetuses are the product of term gestations. In general, nearly 95% of fetuses gain 12.7 ± 2.8 g/day from 37-42 weeks' gestation, indicating that an average fetus gains an additional 445 ± 98 g (1 lb ± 3 oz) during this period. If a patient is thought to have a term fetus weighing >4000 g and if she is willing to undergo labor induction, effecting vaginal delivery rather than awaiting spontaneous labor and an increased average birth weight at delivery is often reasonable.

In studies designed to examine this question, labor induction has not conclusively decreased fetal and maternal risks of intrapartum complications. Data from several studies suggested that the cesarean-delivery rate increased, whereas the rate seemed unchanged in others. The difficulty in interpreting these results are the considerable differences among the predicted and actual birth weights for patients examined, and the power of the studies has been insufficient to conclusively demonstrate statistically significant differences in adverse fetal outcomes among different groups.

As with the case of preterm delivery of underweight fetuses, many considerations, including the size of the maternal pelvis and the weight of previously delivered fetuses, should be considered when fetuses are too large. Clinical judgment in these circumstances is paramount in deciding whether labor induction is indicated to minimize excessive fetal weight at delivery.

Conclusions

Both low birth weight (<2500 g) and high birth weight (>4000 g) are fetal conditions associated with increased risks of peripartum morbidity and mortality. Although the absolute risk that fetuses with birth weights of 2000-2500 g or 4000-4500 g will have major peripartum complications is not overwhelming, the risk substantially increases with decreasing and increasing birth weight relative to these limits. Therefore, birth weight and gestational age are both important determinants of peripartum outcome. From this standpoint, the optimal range of newborn weight is generally thought to be 3000-4000 g (6 lb 10 oz to 8 lb 13 oz). As always, the problem is knowing the fetal weight with sufficient accuracy in advance of delivery.

Many factors that directly affect birth weight are not modifiable. These include maternal race, height, parity, paternal height, and fetal sex. Modifiable factors with potentially important effects on birth weight are prepregnancy weight, pregnancy weight gain, glucose control in patients with diabetes or glucose intolerance of pregnancy, maternal hemoglobin concentration, and gestational age at delivery.

Although the delivery of fetuses that weigh 2000-2499 g is typically not associated with an overwhelming increase in neonatal complications compared with normal-weight neonates, fetuses weighing <2000 g at birth are at increased risk for perinatal complications that is commensurate with their weight.

Although allowing a trial of a vaginal delivery for a fetus estimated to weigh 4000-4500 g may be reasonable in many circumstances, many sources suggest that fetuses with estimated weights of 4500 g or greater (or >4250 g in women with gestational diabetes) should be delivered by means of cesarean section to avoid the increased intrapartum risks associated with the vaginal delivery of a macrosomic fetus. This recommendation is especially true in gestational diabetes, when the fetal conformation may be altered to reflect an enlarged shoulder girdle or HC ratio compared with that of the offspring of mothers without diabetes.

In the case of macrosomic fetuses, attempts to predict birth weight from fetal measurements on ultrasonography have been unsuccessful in improving clinical outcomes. Many researchers have concluded that ultrasonographic fetal biometric assessments are no more predictive of fetal macrosomia than clinical assessments of fetal size by means of simple external abdominal palpation (see Table 6, Table 18, Table 19, and Table 20). Both ultrasonography and manual assessment of fetal size have sensitivities of <60% for fetal macrosomia, with false-positive rates >40%. Likewise, for small fetuses <1800 g, ultrasonographic estimates of fetal weight are often wrong by as much as 25%.

By using birth-weight prediction equations based on parental and pregnancy-specific characteristics alone, fetal weight at and near term can be predicted with a high degree of accuracy (±7.6-8.4%). In healthy pregnant women, this approach is at least as reliable as clinical palpation and ultrasonographic fetal biometry in predicting fetal macrosomia (see Table 12, Table 13, Table 14, Table 18, Table 20, and Media file 3); neither palpation nor ultrasonographic fetal biometry can be used with any degree of certainty in advance of delivery.

Such a quantitative assessment of maternal characteristics serves to objectively quantify most previously recognized clinical variables that have long been used in subjective clinical assessments and that are thought to be predictive of fetal weight.

By contrast, clinical palpation is a subjective method that must be applied at or near the date of delivery, and its success depends on both the patient and the clinician. This method is less accurate in obese than in nonobese pregnant women, and predictions of birth weight have considerable interobserver variations even among experienced clinicians.

The disadvantages of ultrasonographic fetal biometry are that the method is complicated, labor intensive, and potentially limited by suboptimal visualization of fetal structures. It also requires costly sonographic equipment and specially trained personnel. Although such expensive imaging equipment is widely available in the United States and in other industrialized countries, it is generally not available in developing nations, where medical resources are often scarce.

By combining the different methods of fetal-weight prediction, overall accuracy can be improved. Quantitative combinations of parental and pregnancy-specific information (of the type incorporated in Equation 1) with the independent information obtained on ultrasonographic fetal biometry (with AC, FL, BPD, and HC) to generate algorithms of the type presented in Equation 2 substantially improve fetal-weight prediction.

A set of 61 such algorithms has been developed with the necessary selection logic to optimize the accuracy of fetal-weight predictions in women of all races and sizes and to optimize the detection of fetal macrosomia. The mean absolute percentage error in fetal-weight predictions by using this new combinatorial technique is ±6.0% (±213 g at term) and significantly better than the accuracy attainable by using any other method. In the case of excessive fetal size, combining these methods results in an 83%

positive predictive value for fetal macrosomia >4000 g, with a sensitivity of 65% and specificity of 95%. The area under the receiver operating characteristic curve for predicting fetal macrosomia is increased to 0.92.

For pregnant women at high risk for fetal macrosomia, the approach of using a birth-weight prediction algorithm that incorporates parental characteristics, pregnancy-specific factors, and ultrasonographic fetal biometric measurements can be used to most accurately estimate fetal weight and the risk of fetal macrosomia.

The advent of 3-dimensional fetal sonography and MRI has generated optimism that these new technologies can improve estimations of fetal weight, but the advantages of these techniques have not yet been demonstrated. Because all current 3-dimensional imaging methods rely on volumetric reconstructions that depend on standard 2-dimensional sections, they theoretically have the same limitations as standard 2-dimensional fetal imaging, and major improvements in accuracy are unlikely to be forthcoming.

As a result of recent improvements in the accuracy of fetal-weight predictions, practicing obstetricians can now undertake prospective interventions more confidently than before, with the aim of minimizing intrapartum and peripartum risks for both fetuses and mothers.

Multimedia

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Media file 1: Photograph of a macrosomic newborn soon after birth.

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Media file 2: Influence of maternal hemoglobin concentration on term birth weight.

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Media file 3: Direct comparison of the predictive accuracy of 25 ultrasonographic fetal biometric equations for predicting birth weight, with a single maternal-characteristics prediction equation.

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Media file 4: Sensitivity and specificity for the prediction of fetal macrosomia greater than 4000 g by using Equation 1. Jagged lines represent results obtained from raw data; curved lines represent smoothed values.

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Media file 5: Curve delineating the trade-off between positive and negative predictive values by using Equation 1.

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Media file 6: Receiver operating characteristics curve for the prediction of fetal weight of greater than 4000 g using Equation 1. Dashed lines represent the sensitivity and specificity associated with prediction equation cutoff values of 3500 g, 3700 g, and 3920 g, respectively.

Keywords

birth weight prediction, estimation of birth weight, low birth weight, excessive fetal weight, fetal macrosomia, excessive birth weight, birth weight estimation, fetal complications, perinatal complications, preterm delivery, parturition, birth, pregnancy, labor, gestation, intrauterine growth restriction, intrauterine growth retardation, IUGR, shoulder dystocia, brachial plexus injuries, bony injuries, intrapartum asphyxia, birth canal injury, pelvic floor injury, postpartum hemorrhage, macrosomic fetus, ultrasonographic fetal biometry, obstetrical ultrasonography

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