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Sonographic fetal weight estimation –
- 1. ORIGINAL ARTICLE
Sonographic fetal weight estimation – is there more to it than just
fetal measurements?
Oshri Barel1,2
, Ron Maymon1,2*, Zvi Vaknin1,2
, Josef Tovbin1,2
and Noam Smorgick1,2
1
Department of Obstetrics and Gynecology, Assaf Harofeh Medical Center, Zerifin, Israel
2
Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
*Correspondence to: Ron Maymon. E-mail: maymonrb@bezeqint.net
ABSTRACT
Objectives The primary aim of this study was to evaluate the effects of different maternal, fetal, and examiner related
factors on the accuracy of sonographic fetal weight estimation (SFWE).
Methods A retrospective cohort study analyzing 9064 SFWEs performed within 1 week prior to delivery, including
singleton pregnancies with a gestational age of 37 to 42 weeks, was recorded at one medical center from January 2004
to 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 accuracy
were assessed. The systematic error, random error, and mean absolute percentage error were used as measures
of accuracy.
Results High maternal weight, height, body mass index, multiparity, older maternal age, diabetes, and fetal male sex
were associated with underestimation of SFWE (P < 0.05). Fetal presentation and the sonographer’s experience
influenced 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 probably
due to inherent problems in SFWE formulas. © 2013 John Wiley & Sons, Ltd.
Funding sources: None
Conflicts of interest: None declared
INTRODUCTION
Ultrasound 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 METHODS
This retrospective cohort study assessed sonographic and
obstetric data of deliveries in Assaf Harofe Medical Center
between January 2004 and September 2011. The study cohort
comprised of parturient women who referred to our
gynecologic and obstetrical ultrasound unit for SFWE within
1 week prior to delivery. Most women were referred for routine
ultrasound exam, because it is customary in our department to
perform such evaluation to each parturient reporting for any
reason during weekday mornings, if such estimation was not
performed in the previous 2 weeks. Inclusion criteria were a
live-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
- 2. and gestational age between 37 and 42 completed weeks.
Exclusion criteria were detection of a fetal abnormality or a
major malformation, active labor at the time of SFWE, or
ruptured membranes.
The computerized database used in our department was
searched to obtain the sonographic fetal measurements taken
within 1 week before delivery. Sonographic fetal measurements,
including biparietal diameter, head circumference, abdominal
circumference, and femur diaphysis length, were performed
according to formal standards.11–13
Amniotic fluid index (AFI)
was measured and recorded in the standard four-quadrant
assessment technique.14
Oligohydramnios was defined as
AFI ≤ 5 cm and polyhydramnios as AFI > 24 cm. Subsequently,
the expected BW was recalculated by using the models by
Sabbagha et al.15
(designed for appropriate for gestational age
fetuses) and Combs et al.,16
which proved to be the most
accurate in our population in a previous study,17
and also by
using the popular model by Hadlock et al.18
(utilizing abdominal
circumference, femur diaphysis length, head circumference, and
biparietal diameter). Those calculated expected BW were
compared with the actual BW, also obtained from the
departmental computerized database.
The SFWEs were performed in our obstetrics ultrasound
unit by ultrasound technicians and by physicians trained
in obstetrics and gynecology. Some physicians received
additional training in obstetrical ultrasound and were defined
in this study as ultrasound specialists.
Additional demographics, clinical data, and sonographic
data were extracted from the patient’s computerized medical
records; these were taken at the time of admission to delivery
(within 1 week following the ultrasound examination) and
included maternal age, maternal height and weight, obstetrical
history, gestational age at delivery, mode of delivery, fetal
presentation, and fetal sex. The gestational age was
determined according to the last menstrual period and the first
trimester ultrasound where available, in patients with no first
trimester ultrasound, the gestational age was corroborated
with the second trimester ultrasound. The gestational age
was corrected when there was a disparity of >6 days between
the last menstrual period and the dating according to the first
trimester ultrasound and >10 days between the last menstrual
period and the dating according to the second trimester
ultrasound. We did not record ethnicity or race because the
rate of intermarriage between individuals of widely different
geographic and ethnic origins is currently high in Israel.
The study was approved by the local Institutional
Review Board.
Statistical analysis
Data were collected on a standard spreadsheet (Microsoft
Excel 2010). Statistical analysis was performed using SPSS
software (Version 15, Chicago, IL, USA) by the Tel Aviv
University statistical laboratory; P-values of <0.05 were considered
statistically significant. Fetal ultrasound measurements were used
in the calculations of the formulas for the models analyzed.
Descriptive parameters are expressed as mean ± standard
deviation. Frequencies are presented as percentages. The
analysis was performed in several ways: percentage error was
calculated by subtracting the actual BW from the calculated
BW and then dividing the difference by the actual BW and
multiplying by 100. The mean percentage error (MPE),
expressing the systematic error, was calculated from the
percentage error. Absolute percentage error and mean absolute
percentage error (MAPE) were calculated the same way by
using the absolute value of the difference between the
estimated BW and the actual BW. Random error, which is the
standard 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 test
in reference to maternal age, parity, weight, height, BMI,
diabetes status, gestational age, time from the ultrasound
examination to delivery, fetal gender, fetal presentation, and
the amount of amniotic fluid. Levene’s test for equality of
variance was used to compare random errors. Multivariate
stepwise linear regression was also performed in order to
evaluate the influence of different variables on SFWE results.
RESULTS
Included in this study were 9064 SFWE estimations performed
during the week prior to delivery (mean time to delivery,
1.6 ± 1.8 days). Total delivery rate in our institute within that
period of time consisted of 74 970 births; 67 149 of them
between 37 and 42 weeks gestational age. The mean maternal
age of our subjects was 30.2 ± 5.0 years (range, 17–48 years),
and the median parity was 2 (range, 1–13). Gestational diabetes
mellitus (GDM) type A1 was recorded in 536 (5.9%) women,
whereas 265 (2.9%) had insulin-dependent gestational or
pregestational diabetes mellitus. The mean newborn weight
at delivery was 3322 ± 467 g (range, 1680–5420 g), and the mean
gestational age at delivery was 39.3 ± 1.2 weeks (range,
37–42 weeks). 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 maternal
characteristics are described in Table 1.
Maternal and gestational characteristics were evaluated in
correlation with BW. Increasing maternal weight, height, BMI,
parity status, and advanced gestational age were all associated
with higher BW (P < 0.001).
The SFWE were evaluated with the model by Sabbagha
et al.15
(which uses gestational age in addition to sonographic
fetal measurements) and with the models by Combs et al.16
and 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 of
sonographic 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/m
2
) 29.1 ± 4.8 (16.4–49.7)
Data are expressed as mean ± standard deviation (range).
Factors affecting SFWE 51
Prenatal Diagnosis 2014, 34, 50–55 © 2013 John Wiley & Sons, Ltd.
- 3. for the total population were 0.7%, 3.8%, and 5.8% using the
models by Sabbagha et al.,15
Combs et al.,16
and Hadlock
et al.17
respectively. Groups were analyzed according to
different variables in order to investigate the effect of each
factor on the accuracy of fetal weight estimation. The factors
we assessed were maternal (weight, height, age, parity,
diabetes status, and BMI), fetal (gender, presentation, AFI,
and actual BW), and the training and experience of the
performer of weight estimation; the results are listed in Table 2.
Multivariate stepwise linear regression demonstrated an
effect of maternal height, BMI, age, maternal diabetes,
gestational age, parity status, and fetal gender as significant
in affecting the MPE of SFWE using the methods by Sabbagha
et al.15
and Combs et al.16
(P < 0.001). All of these factors except
maternal age and BMI were found to significantly affect the
weight estimation using the method by Hadlock et al.18
The
summary of the influence of each factor on the results of fetal
weight estimation is presented in Table 3. Nevertheless,
although many of the factors we assessed were found to be
significant, the coefficient of determination (R2
) was 0.042 for
Hadlock et al.,18
0.044 for Combs et al.,16
and 0.097 for
Sabbagha et al.;15
meaning that only 4.2% to 9.7% of the
difference in systematic errors could be attributed to those
variables, and more than 90% was caused by other factors.
Regarding maternal characteristics, maternal weight and
height were found to influence the SFWE, with increasing
maternal weight and height causing an underestimation of
the SFWE using the models by Sabbagha et al.15 and by Combs
et al.15,16
(P < 0.001 for both weight and height).The BMI also
influenced the SFWE in the same way (P < 0.001), although
the actual difference was less than 1% (Table 2). Maternal
diabetes was associated with an underestimation of fetal
weight, with an estimation of 2.6% to 2.7% less than the actual
BW in GDM-A1 and insulin-dependent diabetes, accordingly,
using the model by Sabbagha et al.15
(P < 0.05). The model by
Combs et al.16
was found to be more accurate for women with
diabetes than for the rest of the population [3.6% overestimation
for women without diabetes vs 2.2% overestimation for GDM-A1
and 2.7% for insulin-dependent diabetes (P < 0.05)]. Maternal
age was also found to be an independent variable affecting SFWE
using the models by Sabbagha et al.15
and by Combs et al.,16
with older age associated with an underestimation of fetal weight
(P< 0.001). The model by Hadlock et al.18
was related with an
overestimation of fetal weight in all of the groups evaluated.
Analysis of the effects of these variables on the results of SFWE
by Hadlock et al.18
demonstrated a small although significant (P
0.001) improvement in accuracy with higher maternal weight,
height, gestational age, and parity status; nevertheless, the
results were still less accurate in our population than the results
with the models by Sabbagha et al.15
and by Combs et al.16
Regarding fetal characteristics, fetal presentation was not found
to significantly affect the systematic error of fetal weight
estimation using both models by Sabbagha et al.15
and by
Combs et al.16
MAPE, which is another measure of expressing
the overall accuracy, was slightly higher for breech and
other non-cephalic presentations (8% and 8.4%, respectively)
compared with cephalic presentations (6.9%), (P< 0.05). Breech
presentation 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 in
SFWE using all three models. The model by Sabbagha et al.15
produced an underestimation of 1.6% in male fetuses weight
estimation while being very accurate for female fetuses, with only
a 0.4% overestimation (P< 0.05). The model by Combs et al.,16
on
the other hand, tended to overestimate all SFWE by 2.8% in male
fetuses and by 4.4% in female fetuses (P< 0.05). The model by
Hadlock et al.18
was associated with an overestimation of 2.8% in
male fetuses and 4.4% in female fetuses (P< 0.05).
The AFI also influenced the SFWE. Oligohydramnios (AFI< 5cm)
was associated with an overestimation, and polyhydramnios
(AFI > 24 cm) was associated with an underestimation of
SFWE in respect to the normal amount of amniotic fluid
using the models by Sabbagha et al.15
and by Combs
et al.16
The model by Hadlock et al.18
was associated with
an overestimation of 5.9% in cases of oligohydramnios, an
overestimation of 3.4% in cases with normal AFI and a
lower 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 with
experience of at least 2 years in our ultrasound unit were found
to have MAPE closer to the actual BW using the models by
Combs et al.16
(P < 0.05) and Hadlock et al.18
However, there
was a significant difference in systematic errors in the SFWE
between those with more than 2 years and those with less than
2 years of experience only with the model by Hadlock et al.18
The SFWE of ultrasound technicians were also compared with
those of physicians with or without specialized ultrasound
training. The SFWE results obtained by physicians were
systematically lower than those obtained by technicians. Using
the model by Combs et al.,16
physicians with ultrasound
specialty had very accurate results with lower systematic errors
than other physicians, and ultrasound technicians had the
highest systematic errors (P < 0.05). The model by Hadlock
et al.18
also demonstrated better accuracy of fetal weight
estimation by US specialists than by physicians and better
accuracy of SFWE performed by physicians than by US
technicians. On the other hand, using the model by Sabbagha
et al.,15
technicians were found to be most accurate, and
ultrasound specialists were the least accurate (P < 0.001).
Although this difference was found statistically significant,
the difference in accuracy between physicians and technicians
was no more than 2.6% to 1.5% using the methods by Combs
et al.16
and Sabbagha et al.,15
respectively.
DISCUSSION
In this retrospective cohort study, we tested more than 9000
fetuses and investigated the effects of different maternal, fetal,
and examiner variables on the accuracy of SFWE. We found
that many factors did affect the SFWE significantly, although
this effect was small, and its clinical significance is questionable.
In particular, increasing maternal height and weight, advanced
gestational age, maternal diabetes, and parity were associated
with an underestimation of fetal weight using the models by
Combs et al.16
and Sabbagha et al.15
and a small improvement
in weight estimation using the model by Hadlock et al.18
These
O. Barel et al.52
Prenatal Diagnosis 2014, 34, 50–55 © 2013 John Wiley & Sons, Ltd.
- 5. factors were also associated with greater BW. This finding may be
explained by regression toward the mean, which is an inherent
mathematical property of SFWE models on the basis of
nonlinear regression analysis. We can therefore assume that,
because all of these factors are associated with larger newborn
weights, the results of SFWE are lower than expected because
of regression toward the mean.
Previous studies have found different effects of fetal sex on
SFWE. Some studies have not described a clear association,2,19
whereas others have not reported an association and even
generated fetal sex specific models for SFWE.20
In the current
study, we have evaluated over 9000 SFWE and have found a
correlation between male gender and an underestimation of
fetal weight using the model by Sabbagha et al.15
On the other
hand, this model is very suitable for female fetuses with a
systematic error of only 0.4% (P < 0.001). The same tendency
was also found using the model by Combs and Hadlock but
with higher systematic errors (Table 2).
There is conflicting evidence regarding the influence of
sonographer’s experience on SFWE. Predanic et al.21
investi-
gated the learning curve in estimating fetal weight; there were
significant improvements in accuracy amongst residents in
training up to 24months, at which time, the best performance
was achieved. Conversely, Ben-Aroya et al.8
claimed that neither
experience nor fatigue influenced the accuracy of fetal weight
estimation performed by residents. We found a significant effect
of sonographer’s experience on the systematic errors only using
the model by Hadlock et al.,18
although a slight impact was also
found in overall accuracy (expressed as MAPE) in favor of more
experienced sonographers with over 24months experience
(P< 0.05) when using the model by Combs et al.16 and Hadlock
et al.16,18
When we compared physicians and technicians, the
systematic error was lower for technicians using the model by
Sabbagha et al.15
with a systematic error of less than 1%
(P< 0.05). There are a few possible explanations for this
phenomenon. First, those pregnancies evaluated by physicians
may have included more complex cases such as intrauterine
growth restriction and macrosomia. This diversity of cases could
increase the margin of error. Second, physicians possibly use
clinical judgment when assessing fetal weight, which may
slightly influence their fetal measurements. The physicians’
SFWE was closer to the actual BW when using the models by
Combs et al.16and Hadlock et al.16,18
but not when using the
model by Sabbagha et al.,15
which is less dependent on the fetal
measurements because gestational age is also a part of the
equation. Random errors were also higher for SFWE performed
by technicians in comparison with those performed by
physicians and ultrasound specialists
Fetal presentation also seemed to affect the accuracy of
SFWE in previous studies by Dammer et al.22
(who investigated
244 fetuses) and by Melamed et al.23
(who investigated 165
cases). We evaluated this hypothesis in 348 cases and found a
significant difference using the model by Hadlock et al.18
We
could not demonstrate a significant impact of breech
presentation on the systematic error using the model by
Combs et al.16 or by Sabbagha et al.15,16
Amniotic fluid index also had an effect on SFWE with a
tendency for overestimation of fetal weight in cases of
oligohydramnion 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 possible
explanation for this finding might be that polyhydramnios
was associated with higher BW, whereas oligohydramnios
was associated with lower BW in our population (P < 0.05),
and the SFWE tended to regress toward the mean thereby
causing this effect.
Our study presents several limitations. This is a retrospective
cohort study, and the data are derived from a facility-
based rather than a population-based registry. This may
undermine the possibility to generalize our conclusions.
One major weakness in this study is that although many
of the variables we studied significantly affect the fetal
weight estimation error, the actual combined contribution
to 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 Sabbagha
Coefficient of determination (R
2
) (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
Prenatal Diagnosis 2014, 34, 50–55 © 2013 John Wiley & Sons, Ltd.
- 6. factors we assessed are only on the tip of the iceberg and
that most causes for SFWE errors are still unaccounted
for. Random errors are still the major causes for the
inherent errors in SFWE, and the factors we evaluated
did not significantly influence these errors.
In conclusion, many maternal, fetal, and examiner related
factors significantly influence the SFWE. Knowledge of the
influence of these factors on the SFWE may help the clinician
to understand whether the fetal weight estimation performed
tends for overestimation or underestimation of the actual
BW, possibly, allowing for improved management of
pregnancy and delivery. Nevertheless, even after adjusting for
these factors, fetal weight estimation will only improve by up
to 10% of systematic errors. Further research has to be
performed in order to find more accurate fetal weight
estimation formulas or other factors that might be accountable
for systematic and random errors.
WHAT’S ALREADY KNOWN ABOUT THIS TOPIC?
• Most of the studies so far found conflicting evidence regarding the
effect of maternal, fetal, and examiner related factors on the
accuracy of sonographic fetal weight estimation.
WHAT DOES THIS STUDY ADD?
• This study evaluated over 9000 cases and found a significant effect
of several factors on the accuracy of sonographic fetal weight
estimation. Nevertheless, even after adjusting for these factors, fetal
weight estimation will only improve by up to 10%.
REFERENCES
1. 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 fetal
weight. Ultrasound Obstet Gynecol 2005;25:80–9.
3. Heer IM, Kumper C, Vogtle N, et al. Analysis of factors influencing the
ultrasonic fetal weight estimation. Fetal Diagn Ther 2008;23:204–10.
4. Blann DW, Prien SD. Estimation of fetal weight before and after
amniotomy in the laboring gravid woman. Am J Obstet Gynecol
2000;182:1117–20.
5. Farrell T, Holmes R, Stone P. The effect of body mass index on three
methods of fetal weight estimation. BJOG 2002;109:651–7.
6. Benacerraf BR, Gelman R, Frigoletto FD Jr. Sonographically estimated
fetal weights: accuracy and limitation. Am J Obstet Gynecol
1988;159:1118–21.
7. Townsend RR, Filly RA, Callen PW, Laros RK. Factors affecting prenatal
sonographic estimation of weight in extremely low birthweight infants. J
Ultrasound Med 1988;7:183–7.
8. Ben-Aroya Z, Segal D, Hadar A, et al. Effect of OB/GYN residents’ fatigue
and training level on the accuracy of fetal weight estimation. Fetal
Diagn Ther 2002;17:177–81.
9. Nahum GG, Stanislaw H, Huffaker BJ. Accurate prediction of term birth
weight from prospectively measurable maternal characteristics. J
Reprod Med 1999;44:705–12.
10. Mazouni C, Rouzier R, Ledu R, et al. Development and internal
validation of a nomogram to predict macrosomia. Ultrasound Obstet
Gynecol 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-quadrant
assessment of amniotic fluid volume: an adjunct to antepartum fetal
heart rate testing. Obstet Gynecol 1987;70:353–6.
15. Sabbagha RE, Minogue J, Tamura RK, Hungerford SA. Estimation of
birth weight by use of ultrasonographic formulas targeted to large-,
appropriate-, and small-for-gestational-age fetuses. Am J Obstet
Gynecol 1989;160:854–60.
16. Combs CA, Jaekle RK, Rosenn B, et al. Sonographic estimation of
fetal weight based on a model of fetal volume. Obstet Gynecol
1993;82:365–70.
17. Barel O, Vaknin Z, Tovbin J, et al. Assessment of accuracy for multiple
sonographic fetal weight estimation formulas: a 10-year experience
from a single center. J Ultrasound Med 2013;32:815–23.
18. Hadlock FP, Harrist RB, Sharman RS, et al. Estimation of fetal weight
with the use of head, body, and femur measurements – a prospective
study. Am J Obstet Gynecol 1985;151:333–7.
19. Ott WJ, Doyle S, Flamm S. Accurate ultrasonic estimation of fetal
weight. Am J Perinatol 1985;2:178–82.
20. Melamed N, Yogev Y, Ben-Haroush A, et al. Does use of a sex-specific
model 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 of
fetal weight: acquiring accuracy in residency. J Ultrasound Med
2002;21:495–500.
22. Dammer U, Goecke TW, Voigt F, et al. Sonographic weight
estimation in fetuses with breech presentation. Arch Gynecol Obstet
2013;287:851–8.
23. Melamed N, Ben-Haroush A, Meizner I, et al. Accuracy of sonographic
fetal weight estimation: a matter of presentation. Ultrasound Obstet
Gynecol 2011;38:418–24.
24. Meyer WJ, Font GE, Gauthier DW, et al. Effect of amniotic fluid
volume on ultrasonic fetal weight estimation. J Ultrasound Med
1995;14:193–7.
Factors affecting SFWE 55
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