Sonographic fetal weight estimation –

ORIGINAL ARTICLE

Sonographic fetal weight estimation – is there more to it than justfetal measurements?Oshri Barel1,2, Ron Maymon1,2*, Zvi Vaknin1,2, Josef Tovbin1,2 and Noam Smorgick1,2

1Department of Obstetrics and Gynecology, Assaf Harofeh Medical Center, Zerifin, Israel2Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel*Correspondence to: Ron Maymon. E-mail: [email protected]

ABSTRACTObjectives The primary aim of this study was to evaluate the effects of different maternal, fetal, and examiner relatedfactors on the accuracy of sonographic fetal weight estimation (SFWE).

Methods A retrospective cohort study analyzing 9064 SFWEs performed within 1week prior to delivery, includingsingleton pregnancies with a gestational age of 37 to 42weeks, was recorded at one medical center from January 2004to September 2011. Predicted birth weights were calculated according to models by Sabbagha et al., Hadlock et al.,and Combs et al. and were compared with the actual birth weight. Effects of different factors on SFWE accuracywere assessed. The systematic error, random error, and mean absolute percentage error were used as measuresof accuracy.

Results High maternal weight, height, body mass index, multiparity, older maternal age, diabetes, and fetal male sexwere associated with underestimation of SFWE (P< 0.05). Fetal presentation and the sonographer’s experienceinfluenced SFWE differently using various models. The amniotic fluid index did have a significant effect on SFWE.Overall, more than 90% of the systematic errors were unaccounted for in the factors we assessed.

Conclusions Many maternal and fetal factors significantly influence the SFWE; nevertheless, most errors are probablydue to inherent problems in SFWE formulas. © 2013 John Wiley & Sons, Ltd.

Funding sources: NoneConflicts of interest: None declared

INTRODUCTIONUltrasound estimation of the fetal weight is one of the most

common ways to assess the growth of a fetus in utero to

evaluate an ongoing pregnancy or to prepare for delivery.

Information regarding intrauterine growth restriction or excess

growth (macrosomia) may influence the pregnancy follow-up

and the timing and mode of delivery. Additionally, knowledge

of the fetal weight is an important factor affecting fetal

mortality.1 However, although numerous methods were

developed to compute the sonographic fetal weight estimation

(SFWE) from fetal measurements, a high random error of more

than 7% characterizes most of them, undermining the

accuracy of the SFWE and possibly affecting clinical decisions

regarding pregnancy follow-up and delivery.2 In addition to

the inherent random errors of these methods, various clinical

and technical factors may affect the accuracy of the SFWE.

These factors may or may not include maternal factors such

as body mass index (BMI);3–5 pregnancy factors such as fetal

sex, multiple pregnancy, and amniotic fluid volume;3,6,7 and

technical factors related to the experience and fatigue of the

ultrasonographer.3,8 Models for prediction of fetal weight using

maternal characteristics with or without combination with

sonographic fetal measurements have also been developed.9,10

Indeed, previous studies have found conflicting results

regarding those various clinical and technical factors and were

performed on a relatively small sample of patients. Thus, the

aim of the current study was to determine the effect of clinical,

sonographic, and technical factors on the accuracy of SFWE in

a large retrospective cohort.

MATERIALS AND METHODSThis retrospective cohort study assessed sonographic andobstetric data of deliveries in Assaf Harofe Medical Centerbetween January 2004 and September 2011. The study cohortcomprised of parturient women who referred to ourgynecologic and obstetrical ultrasound unit for SFWE within1week prior to delivery. Most women were referred for routineultrasound exam, because it is customary in our department toperform such evaluation to each parturient reporting for anyreason during weekday mornings, if such estimation was notperformed in the previous 2weeks. Inclusion criteria were alive-birth singleton pregnancy, birth weight (BW) over 1500 g,

Prenatal Diagnosis 2014, 34, 50–55 © 2013 John Wiley & Sons, Ltd.

DOI: 10.1002/pd.4250

and gestational age between 37 and 42 completed weeks.Exclusion criteria were detection of a fetal abnormality or amajor malformation, active labor at the time of SFWE, orruptured membranes.

The computerized database used in our department wassearched to obtain the sonographic fetal measurements takenwithin 1week before delivery. Sonographic fetal measurements,including biparietal diameter, head circumference, abdominalcircumference, and femur diaphysis length, were performedaccording to formal standards.11–13 Amniotic fluid index (AFI)was measured and recorded in the standard four-quadrantassessment technique.14 Oligohydramnios was defined asAFI≤ 5 cm and polyhydramnios as AFI> 24 cm. Subsequently,the expected BW was recalculated by using the models bySabbagha et al.15 (designed for appropriate for gestational agefetuses) and Combs et al.,16 which proved to be the mostaccurate in our population in a previous study,17 and also byusing the popular model by Hadlock et al.18 (utilizing abdominalcircumference, femur diaphysis length, head circumference, andbiparietal diameter). Those calculated expected BW werecompared with the actual BW, also obtained from thedepartmental computerized database.

The SFWEs were performed in our obstetrics ultrasoundunit by ultrasound technicians and by physicians trainedin obstetrics and gynecology. Some physicians receivedadditional training in obstetrical ultrasound and were definedin this study as ultrasound specialists.

Additional demographics, clinical data, and sonographicdata were extracted from the patient’s computerized medicalrecords; these were taken at the time of admission to delivery(within 1week following the ultrasound examination) andincluded maternal age, maternal height and weight, obstetricalhistory, gestational age at delivery, mode of delivery, fetalpresentation, and fetal sex. The gestational age wasdetermined according to the last menstrual period and the firsttrimester ultrasound where available, in patients with no firsttrimester ultrasound, the gestational age was corroboratedwith the second trimester ultrasound. The gestational agewas corrected when there was a disparity of >6 days betweenthe last menstrual period and the dating according to the firsttrimester ultrasound and >10 days between the last menstrualperiod and the dating according to the second trimesterultrasound. We did not record ethnicity or race because therate of intermarriage between individuals of widely differentgeographic and ethnic origins is currently high in Israel.

The study was approved by the local InstitutionalReview Board.

Statistical analysisData were collected on a standard spreadsheet (MicrosoftExcel 2010). Statistical analysis was performed using SPSS

software (Version 15, Chicago, IL, USA) by the Tel AvivUniversity statistical laboratory;P-values of<0.05were consideredstatistically significant. Fetal ultrasoundmeasurements were usedin the calculations of the formulas for the models analyzed.

Descriptive parameters are expressed as mean± standarddeviation. Frequencies are presented as percentages. Theanalysis was performed in several ways: percentage error was

calculated by subtracting the actual BW from the calculatedBW and then dividing the difference by the actual BW andmultiplying by 100. The mean percentage error (MPE),expressing the systematic error, was calculated from thepercentage error. Absolute percentage error and mean absolutepercentage error (MAPE) were calculated the same way byusing the absolute value of the difference between theestimated BW and the actual BW. Random error, which is thestandard deviation of MPE, was also calculated.

Percentage errors were compared using the Student’s t-test,the Pearson’s correlation test, and the analysis of variance testin reference to maternal age, parity, weight, height, BMI,diabetes status, gestational age, time from the ultrasoundexamination to delivery, fetal gender, fetal presentation, andthe amount of amniotic fluid. Levene’s test for equality ofvariance was used to compare random errors. Multivariatestepwise linear regression was also performed in order toevaluate the influence of different variables on SFWE results.

RESULTSIncluded in this study were 9064 SFWE estimations performedduring the week prior to delivery (mean time to delivery,1.6 ± 1.8 days). Total delivery rate in our institute within thatperiod of time consisted of 74 970 births; 67 149 of thembetween 37 and 42weeks gestational age. The mean maternalage of our subjects was 30.2 ± 5.0 years (range, 17–48 years),and the median parity was 2 (range, 1–13). Gestational diabetesmellitus (GDM) type A1 was recorded in 536 (5.9%) women,whereas 265 (2.9%) had insulin-dependent gestational orpregestational diabetes mellitus. The mean newborn weightat delivery was 3322 ± 467 g (range, 1680–5420 g), and the meangestational age at delivery was 39.3 ± 1.2weeks (range,37–42weeks). A cephalic presentation was recorded in 8689(95.8%) fetuses, a breech presentation in 348 (3.8%) fetuses,and other presentations in 27 (0.3%) fetuses. Other maternalcharacteristics are described in Table 1.

Maternal and gestational characteristics were evaluated incorrelation with BW. Increasing maternal weight, height, BMI,parity status, and advanced gestational age were all associatedwith higher BW (P< 0.001).

The SFWE were evaluated with the model by Sabbaghaet al.15 (which uses gestational age in addition to sonographicfetal measurements) and with the models by Combs et al.16and Hadlock et al.16,18 (which use only fetal measurements)and were compared with the actual BW. The systematic errors

Table 1 The maternal characteristics of 9064 cases ofsonographic fetal weight estimation included in the study

Maternal characteristics Result

Maternal age (years) 30.2 ±5 (17–48)

Parity 2.1 ±1.3 (1–13)

Maternal weight (kg) 78±14.1 (42–150)

Maternal height (m) 1.63±0.06 (1.38–1.83)

Maternal body mass index (kg/m2) 29.1 ±4.8 (16.4–49.7)

Data are expressed as mean ± standard deviation (range).

Factors affecting SFWE 51


for the total population were 0.7%, 3.8%, and 5.8% using themodels by Sabbagha et al.,15 Combs et al.,16 and Hadlocket al.17 respectively. Groups were analyzed according todifferent variables in order to investigate the effect of eachfactor on the accuracy of fetal weight estimation. The factorswe assessed were maternal (weight, height, age, parity,diabetes status, and BMI), fetal (gender, presentation, AFI,and actual BW), and the training and experience of theperformer of weight estimation; the results are listed in Table 2.

Multivariate stepwise linear regression demonstrated aneffect of maternal height, BMI, age, maternal diabetes,gestational age, parity status, and fetal gender as significantin affecting the MPE of SFWE using the methods by Sabbaghaet al.15 and Combs et al.16 (P< 0.001). All of these factors exceptmaternal age and BMI were found to significantly affect theweight estimation using the method by Hadlock et al.18 Thesummary of the influence of each factor on the results of fetalweight estimation is presented in Table 3. Nevertheless,although many of the factors we assessed were found to besignificant, the coefficient of determination (R2) was 0.042 forHadlock et al.,18 0.044 for Combs et al.,16 and 0.097 forSabbagha et al.;15 meaning that only 4.2% to 9.7% of thedifference in systematic errors could be attributed to thosevariables, and more than 90% was caused by other factors.

Regarding maternal characteristics, maternal weight andheight were found to influence the SFWE, with increasingmaternal weight and height causing an underestimation ofthe SFWE using the models by Sabbagha et al.15 and by Combset al.15,16 (P< 0.001 for both weight and height).The BMI alsoinfluenced the SFWE in the same way (P< 0.001), althoughthe actual difference was less than 1% (Table 2). Maternaldiabetes was associated with an underestimation of fetalweight, with an estimation of 2.6% to 2.7% less than the actualBW in GDM-A1 and insulin-dependent diabetes, accordingly,using the model by Sabbagha et al.15 (P< 0.05). The model byCombs et al.16 was found to be more accurate for women withdiabetes than for the rest of the population [3.6% overestimationfor womenwithout diabetes vs 2.2% overestimation for GDM-A1and 2.7% for insulin-dependent diabetes (P< 0.05)]. Maternalagewas also found to be an independent variable affecting SFWEusing the models by Sabbagha et al.15 and by Combs et al.,16

with older age associatedwith an underestimation of fetal weight(P< 0.001). The model by Hadlock et al.18 was related with anoverestimation of fetal weight in all of the groups evaluated.Analysis of the effects of these variables on the results of SFWEby Hadlock et al.18 demonstrated a small although significant (P0.001) improvement in accuracy with higher maternal weight,height, gestational age, and parity status; nevertheless, theresults were still less accurate in our population than the resultswith the models by Sabbagha et al.15 and by Combs et al.16

Regarding fetal characteristics, fetal presentation was not foundto significantly affect the systematic error of fetal weightestimation using both models by Sabbagha et al.15 and byCombs et al.16 MAPE, which is another measure of expressingthe overall accuracy, was slightly higher for breech andother non-cephalic presentations (8% and 8.4%, respectively)compared with cephalic presentations (6.9%), (P< 0.05). Breechpresentation was associated with a slight improvement in

accuracy using the model by Hadlock et al.18 (P< 0.05).Conversely, fetal gender was found to be a significant factor inSFWE using all three models. The model by Sabbagha et al.15

produced an underestimation of 1.6% in male fetuses weightestimation while being very accurate for female fetuses, with onlya 0.4% overestimation (P< 0.05). The model by Combs et al.,16 onthe other hand, tended to overestimate all SFWE by 2.8% in malefetuses and by 4.4% in female fetuses (P< 0.05). The model byHadlock et al.18 was associated with an overestimation of 2.8% inmale fetuses and 4.4% in female fetuses (P< 0.05).

TheAFI also influenced the SFWE.Oligohydramnios (AFI< 5cm)was associated with an overestimation, and polyhydramnios(AFI> 24 cm) was associated with an underestimation ofSFWE in respect to the normal amount of amniotic fluidusing the models by Sabbagha et al.15 and by Combset al.16 The model by Hadlock et al.18 was associated withan overestimation of 5.9% in cases of oligohydramnios, anoverestimation of 3.4% in cases with normal AFI and alower overestimation of 2.9% in cases of polyhydramnios(P< 0.05).

We then sought to evaluate the effect of sonographers’experience on the accuracy of SFWE. Sonographers withexperience of at least 2 years in our ultrasound unit were foundto have MAPE closer to the actual BW using the models byCombs et al.16 (P< 0.05) and Hadlock et al.18 However, therewas a significant difference in systematic errors in the SFWEbetween those with more than 2 years and those with less than2 years of experience only with the model by Hadlock et al.18

The SFWE of ultrasound technicians were also compared withthose of physicians with or without specialized ultrasoundtraining. The SFWE results obtained by physicians weresystematically lower than those obtained by technicians. Usingthe model by Combs et al.,16 physicians with ultrasoundspecialty had very accurate results with lower systematic errorsthan other physicians, and ultrasound technicians had thehighest systematic errors (P< 0.05). The model by Hadlocket al.18 also demonstrated better accuracy of fetal weightestimation by US specialists than by physicians and betteraccuracy of SFWE performed by physicians than by UStechnicians. On the other hand, using the model by Sabbaghaet al.,15 technicians were found to be most accurate, andultrasound specialists were the least accurate (P< 0.001).Although this difference was found statistically significant,the difference in accuracy between physicians and technicianswas no more than 2.6% to 1.5% using the methods by Combset al.16 and Sabbagha et al.,15 respectively.

DISCUSSIONIn this retrospective cohort study, we tested more than 9000fetuses and investigated the effects of different maternal, fetal,and examiner variables on the accuracy of SFWE. We foundthat many factors did affect the SFWE significantly, althoughthis effect was small, and its clinical significance is questionable.In particular, increasing maternal height and weight, advancedgestational age, maternal diabetes, and parity were associatedwith an underestimation of fetal weight using the models byCombs et al.16 and Sabbagha et al.15 and a small improvementin weight estimation using the model by Hadlock et al.18 These

O. Barel et al.52


Table2

Factorsaffectingsono

grap

hicfetalw

eigh

testimation

Factor

Syste

maticerror

(MPE

)by

Sabb

agha

(%)

Syste

matic

error(M

PE)

byCom

bs(%)

Syste

matic

error(M

PE)

byHad

lock

(%)

Rand

omerrorby

Com

bsRa

ndom

errorby

Sabb

agha

Rand

omerrorby

Had

lock

MAPE

bySa

bbag

ha(%)

MAPE

byCom

bs(%)

MAPE

byHad

lock

(%)

Fetal presentation

Cep

halic

(N=86

89)

�0.6

3.5

6.6*

7.9

8.2

8.1

6.3

6.9*

8.3

Breech

(N=34

8)�1

.54.2

5.1*

8.2

9.1

8.2

6.7

8.0*

7.7

Other

(N=27

)�1

.05.5

8.3*

7.7

9.0

7.4

6.1

8.4*

9.1

Amniotic

fluid

inde

xOligoh

ydramnios

(N=38

1)2.2*

5.9*

8.6*

8.1

8.3

8.4

6.6*

8.2*

9.9*

Normal

(N=83

44)

�0.7*

3.4*

6.4*

7.7

8.0

8.1

6.1*

6.8*

8.2*

Polyhydram

nios

(N=33

9)�2

.3*

2.9*

6.8*

7.8

8.0

8.1

6.5*

6.7*

8.5*

Fetalg

ende

rMale(N

=46

61)

�1.6*

2.8*

5.8*

7.6

7.9

7.9

6.2

6.5*

7.8*

Female(N

=44

403)

0.4*

4.4*

7.2*

7.9

8.2

8.3

6.2

7.2*

8.8*

Materna

ldiab

etes

Nodiab

etes

(N=82

63)

�0.5*

3.6*

6.6*

7.9

8.2

8.3

6.1

6.8

8.1

GDM-A1(N

=53

6)�2

.6*

2.2*

5.7*

7.9

8.7

7.9

6.6

6.7

8.2

Insulin-trea

teddiab

etes

(N=26

5)�2

.7*

2.7*

5.9*

8.5

9.7

8.2

6.5

7.1

8.4

Exam

iner

Technician

(N=83

62)

�0.9*

3.8*

6.8*

12.5*

13.1*

8.5

6.3

6.9

8.5

Physician(N

=30

1)�1

.8*

2.4*

4.8*

8.3*

8.7*

8.2

6.9

7.2

8.2

USspecialist(N

=40

1)�2

.4*

1.3*

4.4*

8.3

9.0

7.8

6.9

7.0

7.8

Exam

iner’s

expe

rience

Less

than

2years

(N=11

31)

�0.3

3.9

6.9*

8.2

8.6

8.5

6.4

7.3*

8.7*

2yearsor

more

(N=79

33)

�0.7

3.5

6.5*

7.7

8.0

8.0

6.1

6.8*

8.3*

Mea

npe

rcentage

error(MPE)rep

resentsthe

syste

maticerroro

feac

hmod

el.M

PEisca

lculated

asthemea

ndifferencebe

tweenfetalw

eigh

testimationan

dac

tualbirth

weigh

t(BW

)divided

bytheac

tualBW

andexpressedinpe

rcent.Mea

nab

solute

percentage

error(MAPE)isc

alculatedas

themea

nab

solutevalueof

thedifferencebe

tweenthefetalw

eigh

testimationan

dac

tual

BWdivide

dby

theac

tual

BWan

dexpressedinpe

rcent.Thesta

ndardde

viationof

MPE

representstherand

omerror.

Rand

omerrorswereco

mpa

redusingLevene’stestfore

quality

ofvaria

ncean

dwereno

tfou

ndto

besig

nifica

ntlydifferent

(P>0.05

)*R

epresentsP<0.05

.



factors were also associatedwith greater BW. Thisfindingmay beexplained by regression toward the mean, which is an inherentmathematical property of SFWE models on the basis ofnonlinear regression analysis. We can therefore assume that,because all of these factors are associated with larger newbornweights, the results of SFWE are lower than expected becauseof regression toward the mean.

Previous studies have found different effects of fetal sex onSFWE. Some studies have not described a clear association,2,19

whereas others have not reported an association and evengenerated fetal sex specific models for SFWE.20 In the currentstudy, we have evaluated over 9000 SFWE and have found acorrelation between male gender and an underestimation offetal weight using the model by Sabbagha et al.15 On the otherhand, this model is very suitable for female fetuses with asystematic error of only 0.4% (P< 0.001). The same tendencywas also found using the model by Combs and Hadlock butwith higher systematic errors (Table 2).

There is conflicting evidence regarding the influence ofsonographer’s experience on SFWE. Predanic et al.21 investi-gated the learning curve in estimating fetal weight; there weresignificant improvements in accuracy amongst residents intraining up to 24months, at which time, the best performancewas achieved. Conversely, Ben-Aroya et al.8 claimed that neitherexperience nor fatigue influenced the accuracy of fetal weightestimation performed by residents. We found a significant effectof sonographer’s experience on the systematic errors only usingthe model by Hadlock et al.,18 although a slight impact was alsofound in overall accuracy (expressed as MAPE) in favor of moreexperienced sonographers with over 24months experience(P< 0.05) when using the model by Combs et al.16 and Hadlocket al.16,18 When we compared physicians and technicians, thesystematic error was lower for technicians using the model bySabbagha et al.15 with a systematic error of less than 1%(P< 0.05). There are a few possible explanations for thisphenomenon. First, those pregnancies evaluated by physiciansmay have included more complex cases such as intrauterine

growth restriction and macrosomia. This diversity of cases couldincrease the margin of error. Second, physicians possibly useclinical judgment when assessing fetal weight, which mayslightly influence their fetal measurements. The physicians’SFWE was closer to the actual BW when using the models byCombs et al.16and Hadlock et al.16,18 but not when using themodel by Sabbagha et al.,15 which is less dependent on the fetalmeasurements because gestational age is also a part of theequation. Random errors were also higher for SFWE performedby technicians in comparison with those performed byphysicians and ultrasound specialists

Fetal presentation also seemed to affect the accuracy ofSFWE in previous studies by Dammer et al.22 (who investigated244 fetuses) and by Melamed et al.23 (who investigated 165cases). We evaluated this hypothesis in 348 cases and found asignificant difference using the model by Hadlock et al.18 Wecould not demonstrate a significant impact of breechpresentation on the systematic error using the model byCombs et al.16 or by Sabbagha et al.15,16

Amniotic fluid index also had an effect on SFWE with atendency for overestimation of fetal weight in cases ofoligohydramnion and underestimation in cases of polyhydramnios(P< 0.001). This finding is in contrast with previous studies,3,6,24

which found no influence of AFI on SFWE. A possibleexplanation for this finding might be that polyhydramnioswas associated with higher BW, whereas oligohydramnioswas associated with lower BW in our population (P< 0.05),and the SFWE tended to regress toward the mean therebycausing this effect.

Our study presents several limitations. This is a retrospectivecohort study, and the data are derived from a facility-based rather than a population-based registry. This mayundermine the possibility to generalize our conclusions.One major weakness in this study is that although manyof the variables we studied significantly affect the fetalweight estimation error, the actual combined contributionto the MPE was less than 10%. This indicates that the

Table 3 Effect of different factors on systematic error using the model by Sabbagha et al.15

Factor Effect on systematic error by SabbaghaCoefficient of determination (R2) (total effect on

systematic error accuracy expressed in %)

Maternal age Underestimation* 0.1

Maternal weight Underestimation* 2

Maternal body mass index Underestimation* 1

Maternal height Underestimation* 3

Parity Underestimation* 0.7

Maternal diabetes Underestimation* 0.2

Gestational age Underestimation* 2.3

Fetal male gender Underestimation* 0.7

Fetal presentation No significant effect

Oligohydramnios Overestimation* 4

Polyhydramnios Underestimation* 4

Sonographers’ experience No significant effect

Ultrasound technicians versus physicians No significant effect

*Represents P<0.001.

O. Barel et al.54


factors we assessed are only on the tip of the iceberg andthat most causes for SFWE errors are still unaccountedfor. Random errors are still the major causes for theinherent errors in SFWE, and the factors we evaluateddid not significantly influence these errors.

In conclusion, many maternal, fetal, and examiner relatedfactors significantly influence the SFWE. Knowledge of theinfluence of these factors on the SFWE may help the clinicianto understand whether the fetal weight estimation performedtends for overestimation or underestimation of the actualBW, possibly, allowing for improved management ofpregnancy and delivery. Nevertheless, even after adjusting forthese factors, fetal weight estimation will only improve by upto 10% of systematic errors. Further research has to beperformed in order to find more accurate fetal weight

estimation formulas or other factors that might be accountablefor systematic and random errors.

WHAT’S ALREADY KNOWN ABOUT THIS TOPIC?

• Most of the studies so far found conflicting evidence regarding theeffect of maternal, fetal, and examiner related factors on theaccuracy of sonographic fetal weight estimation.

WHAT DOES THIS STUDY ADD?

• This study evaluated over 9000 cases and found a significant effectof several factors on the accuracy of sonographic fetal weightestimation. Nevertheless, even after adjusting for these factors, fetalweight estimation will only improve by up to 10%.

REFERENCES1. Barker DJP. Long-term outcome of retarded fetal growth. In Clinical

Obstetrics and Gynecology, Divon MY (ed.). Philadelphia, PA:Lippincott–Raven, 1997;853–63.

2. Dudley NJ. A systematic review of the ultrasound estimation of fetalweight. Ultrasound Obstet Gynecol 2005;25:80–9.

3. Heer IM, Kumper C, Vogtle N, et al. Analysis of factors influencing theultrasonic fetal weight estimation. Fetal Diagn Ther 2008;23:204–10.

4. Blann DW, Prien SD. Estimation of fetal weight before and afteramniotomy in the laboring gravid woman. Am J Obstet Gynecol2000;182:1117–20.

5. Farrell T, Holmes R, Stone P. The effect of body mass index on threemethods of fetal weight estimation. BJOG 2002;109:651–7.

6. Benacerraf BR, Gelman R, Frigoletto FD Jr. Sonographically estimatedfetal weights: accuracy and limitation. Am J Obstet Gynecol1988;159:1118–21.

7. Townsend RR, Filly RA, Callen PW, Laros RK. Factors affecting prenatalsonographic estimation of weight in extremely low birthweight infants. JUltrasound Med 1988;7:183–7.

8. Ben-Aroya Z, Segal D, Hadar A, et al. Effect of OB/GYN residents’ fatigueand training level on the accuracy of fetal weight estimation. FetalDiagn Ther 2002;17:177–81.

9. Nahum GG, Stanislaw H, Huffaker BJ. Accurate prediction of term birthweight from prospectively measurable maternal characteristics. JReprod Med 1999;44:705–12.

10. Mazouni C, Rouzier R, Ledu R, et al. Development and internalvalidation of a nomogram to predict macrosomia. Ultrasound ObstetGynecol 2007;29:544–9.

11. Chitty LS, Altman DG, Henderson A, Campbell S. Charts of fetal size, 2:head measurements. Br J Obstet Gynaecol 1994;101:35–43.

12. Chitty LS, Altman DG, Henderson A, Campbell S. Charts of fetal size, 3:abdominal measurements. Br J Obstet Gynaecol 1994;101:125–31.

13. Chitty LS, Altman DG, Henderson A, Campbell S. Charts of fetal size, 4:femur length. Br J Obstet Gynaecol 1994;101:132–5.

14. Rutherford SE, Phelan JP, Smith CV, Jacobs N. The four-quadrantassessment of amniotic fluid volume: an adjunct to antepartum fetalheart rate testing. Obstet Gynecol 1987;70:353–6.

15. Sabbagha RE, Minogue J, Tamura RK, Hungerford SA. Estimation ofbirth weight by use of ultrasonographic formulas targeted to large-,appropriate-, and small-for-gestational-age fetuses. Am J ObstetGynecol 1989;160:854–60.

16. Combs CA, Jaekle RK, Rosenn B, et al. Sonographic estimation offetal weight based on a model of fetal volume. Obstet Gynecol1993;82:365–70.

17. Barel O, Vaknin Z, Tovbin J, et al. Assessment of accuracy for multiplesonographic fetal weight estimation formulas: a 10-year experiencefrom a single center. J Ultrasound Med 2013;32:815–23.

18. Hadlock FP, Harrist RB, Sharman RS, et al. Estimation of fetal weightwith the use of head, body, and femur measurements – a prospectivestudy. Am J Obstet Gynecol 1985;151:333–7.

19. Ott WJ, Doyle S, Flamm S. Accurate ultrasonic estimation of fetalweight. Am J Perinatol 1985;2:178–82.

20. Melamed N, Yogev Y, Ben-Haroush A, et al. Does use of a sex-specificmodel improve the accuracy of sonographic weight estimation?Ultrasound Obstet Gynecol 2012;39:549–57.

21. Predanic M, Cho A, Ingrid F, Pellettieri J. Ultrasonographic estimation offetal weight: acquiring accuracy in residency. J Ultrasound Med2002;21:495–500.

22. Dammer U, Goecke TW, Voigt F, et al. Sonographic weightestimation in fetuses with breech presentation. Arch Gynecol Obstet2013;287:851–8.

23. Melamed N, Ben-Haroush A, Meizner I, et al. Accuracy of sonographicfetal weight estimation: a matter of presentation. Ultrasound ObstetGynecol 2011;38:418–24.

24. Meyer WJ, Font GE, Gauthier DW, et al. Effect of amniotic fluidvolume on ultrasonic fetal weight estimation. J Ultrasound Med1995;14:193–7.



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