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Keywords:

  • accuracy;
  • comparison;
  • estimation;
  • fetal;
  • gender;
  • models;
  • sex;
  • weight

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. REFERENCES

Objectives

To determine whether the accuracy of sonographic fetal weight estimation is related to fetal sex.

Methods

The accuracy of sonographic fetal weight estimation was compared between male and female fetuses using 3672 sonographic weight estimations performed within 3 days prior to delivery. Fetal weight was estimated using eight regression models that are based on different combinations of the following biometric parameters: abdominal circumference (AC), femur diaphysis length (FL), biparietal diameter (BPD) and head circumference (HC).

Results

In seven out of the eight models tested, the presence of a male fetus was associated with a significantly lower systematic error compared with a female fetus (−0.2 to 2.1% vs. 1.3 to 6%, P < 0.001). On multivariate analysis, fetal sex was independently associated with sonographic accuracy so that the likelihood of a weight estimation within 10% of birth weight was 30% higher for male fetuses compared with female fetuses. The biometric parameters that contributed most to these sex-related differences were FL and AC, while models that included HC were associated with the lowest differences in the systematic error between male fetuses and female fetuses. For most models, the random error and correlation between estimated weight and birth weight were not affected by fetal sex (8.1–12.8% vs. 8.2–13.6%, and 0.856–0.944 vs. 0.842–0.944, respectively).

Conclusion

Sonographic estimation of fetal weight is more accurate for male fetuses than for female fetuses. The use of sex-specific models may improve the accuracy of fetal weight estimation for female fetuses. Copyright © 2011 ISUOG. Published by John Wiley & Sons, Ltd.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. REFERENCES

Accurate estimation of fetal weight has an important role in routine antenatal care and in the detection of fetal growth abnormalities1, 2. For that reason, much effort has been invested in generating models that can accurately predict fetal weight. These regression models are based on various combinations of sonographically measured fetal biometric parameters, mainly abdominal circumference (AC), femur diaphysis length (FL), biparietal diameter (BPD) and head circumference (HC).

It has been previously shown that significant differences in intrauterine growth exist between male and female fetuses3, 4. These sex-specific growth patterns may result in differences in the correlation between the various biometric parameters and actual birth weight in male fetuses compared with female fetuses, and thus to differences in the accuracy of a given sonographic model in the prediction of birth weight for male fetuses compared with female fetuses. This information regarding sex-specific accuracy of weight estimation may be of great importance, especially in cases in which fetal growth abnormalities are suspected, and can provide support to the development of sex-specific sonographic models for fetal weight estimation.

Nevertheless, none of the widely accepted sonographic models for fetal weight estimation5–10 considers fetal sex in the equation. Furthermore, there are only limited data on whether the use of such sex-independent sonographic models results in different degrees of accuracy of weight estimation in male fetuses compared with female fetuses11.

Therefore, the aim of the present study was to test our hypothesis that the accuracy of sonographic fetal weight estimation may be related to fetal sex.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. REFERENCES

Data collection

A retrospective cohort study design was used. Data were collected from a comprehensive database of sonographic examinations at a single center. Routine sonographic evaluations included the standard fetal biometry measurements (AC, FL, BPD and HC), and the findings were saved directly in the database. Antenatal data, gestational age at delivery, fetal sex and actual birth weights were obtained from the hospital's perinatal database. The study was approved by the local Institutional Review Board.

Study population

The database was searched for all sonographic fetal weight estimations performed within 3 days prior to delivery between 2002 and 2008. Inclusion criteria for the study were live-birth singleton pregnancy, birth weight > 500 g, gestational age > 24 weeks and absence of fetal malformations or hydrops. Pregnancies complicated by gestational or pregestational diabetes, women in active labor or with ruptured membranes, and cases in which not all four biometric parameters were recorded, were excluded.

Definitions

Gestational age at the time of examination was recorded in the database along with the details of the sonographic examination and was calculated from the date of the last menstrual period (LMP). When first-trimester ultrasound results were available, the LMP was corrected based on the crown–rump length (CRL) when the discrepancy between the calculated LMP (based on the Hadlock's CRL reference tables12) and the reported LMP exceeded 7 days, according to the recommendations of the American College of Obstetricians and Gynecologists (ACOG)13. The gestational age at the time of examination was further verified by comparing the interval (in days) between the ultrasound-examination date and the delivery date with the interval between gestational age at the time of examination and gestational age at delivery (the latter was available from the perinatal database). As these intervals are expected to be identical (considering that the gestational age in both cases should have been calculated using the same LMP), cases in which the difference between these intervals was greater than 1 day were excluded. Birth weight percentiles were determined using the local birth weight curves14.

All sonographic fetal weight estimations were performed in our ultrasound unit. Weight estimations were performed by senior physicians specialized in ultrasonography or by experienced ultrasound technicians. In the latter case, the examination was reviewed and signed by a senior physician. The examinations were performed transabdominally using the following ultrasound systems: Voluson E8 and Voluson 730 Expert (GE Medical Systems, Zipf, Austria) and ATL 5000 (Philips Healthcare, Eindhoven, The Netherlands).

The BPD was measured from the proximal echo of the fetal skull to the proximal edge of the deep border (outer–inner) at the level of the cavum septi pellucidi. The HC was measured as an ellipse around the perimeter of the fetal skull15. The AC was measured in the transverse plane of the fetal abdomen at the level of the umbilical vein in the anterior third and the stomach bubble in the same plane; measurements were taken around the perimeter16. The FL was measured in a view where the full femoral diaphysis was seen and was taken from one end of the diaphysis to the other, not including the distal femoral epiphysis17. The cephalic index was calculated as the ratio between the BPD and the occipitofrontal diameter (OFD)18.

The routine sonographic examination does not include the determination of fetal sex, so the sonographers were blinded to the fetal sex during the process of sonographic weight estimation.

Sonographic models

In order to determine the possible contribution of each of the various biometric parameters (i.e. AC, FL, BPD and HC) to the sex-related differences in the accuracy of sonographic fetal weight estimation, we calculated the estimated fetal weight (EFW) using eight regression models published in the literature that are based on different combinations of fetal biometric parameters (Table 1).

Table 1. Models used for sonographic fetal weight estimation
ModelReferenceBiometric measuresEquation
  1. Weight is expressed in g and biometric parameters in cm, except for Model 1 (Warsof), in which weight is expressed in kg and FL is expressed in mm. AC, abdominal circumference; BPD, biparietal diameter; BW, birth weight; EFW, estimated fetal weight; FL, femur diaphysis length; HC, head circumference.

1Warsof et al. (1986)8FLLn BW = 4.6914 + 0.00151(FL)2 − 0.0000119(FL)3
2Hadlock et al. (1984)6ACLn BW = 2.695 + 0.253(AC) − 0.00275(AC)2
3Hadlock et al. (1985)7AC and FLLog10 EFW = 1.304 + 0.05281(AC) + 0.1938(FL) − 0.004(AC)(FL)
4Hadlock et al. (1984)6AC and BPDLog10 EFW = 1.1134 + 0.05845(AC) − 0.000604(AC)2 − 0.007365(BPD)2 + 0.000595(BPD)(AC) + 0.1694(BPD)
5Hadlock et al. (1984)6AC and HCLog10 EFW = 1.182 + 0.0273(HC) + 0.07057(AC) − 0.00063(AC)2 − 0.0002184(HC)(AC)
6Hadlock et al. (1985)7AC, FL and BPDLog10 EFW = 1.335 − 0.0034(AC)(FL) + 0.0316(BPD) + 0.0457(AC) + 0.1623(FL)
7Hadlock et al. (1985)7AC, FL and HCLog10 EFW = 1.326 − 0.00326(AC)(FL) + 0.0107(HC) + 0.0438(AC) + 0.158(FL)
8Hadlock et al. (1985)7AC, FL, BPD and HCLog10 EFW = 1.3596 + 0.0064(HC) + 0.0424(AC) + 0.174(FL) + 0.00061(BPD)(AC) − 0.00386(AC)(FL)

Measures of accuracy

The accuracy of fetal weight estimations (using each of the eight models) in male and female fetuses was compared using the following measures of accuracy: (a) correlation with actual birth weight (using Pearson's correlation coefficient); (b) systematic error (also known as mean percentage error) (mean of (EFW − BW)/BW × 100), which reflects the systematic deviation of a model from the actual birth weight, expressed as a percentage of the actual birth weight; (c) random error (SD of the systematic error × 100)—a measure of precision (rather than accuracy) that reflects the random (or non-systematic) component of the prediction error; and (d) the fraction of estimates within 10% of the actual birth weight.

Statistical analysis

Data analysis was performed using the SPSS v.15.0 software (SPSS Inc., Chicago, IL, USA). The one-sample t-test was used to assess whether the systematic errors were significantly different from zero. Comparison of the characteristics of the male and female groups was performed using the Student's t-test for normally distributed continuous variables, the Mann–Whitney U-test for non-normally distributed continuous variables (gestational age at delivery and interval between sonographic evaluation and delivery) and the chi-square test for categorical data. Comparison of the measures of accuracy between male and female fetuses was performed using the Student's t-test for the systematic error, Levene's test (equality of variance) for the random error, the chi-square test for the fraction of estimates within 10% of the actual birth weight and the Fisher's Z transformation for the correlation between estimated and actual birth weights19. All criteria for the use of the different statistical tests were fulfilled. Multivariate logistic regression analysis was used to determine whether the association of fetal sex and accurate weight estimation (defined as an estimate within 10% of the actual birth weight) is significant and independent of the effects of potential confounders, including those variables that have been previously reported to affect the accuracy of fetal weight estimation (e.g. the time interval between weight estimation and delivery11, gestational age20, 21, parity22 and fetal presentation23) and variables that were found to be significantly different for male and female fetuses in the current study (i.e. birth weight and cephalic index). Differences were considered significant when P < 0.05.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. REFERENCES

Characteristics of the study group

A total of 3672 fetal weight estimations (of 1954 male fetuses and 1718 female fetuses) met the inclusion criteria. The demographic and obstetric characteristics of the women in the study are presented in Table 2. Most of the weight estimations (∼66%) were performed within a 24-h period before delivery. The male and the female groups were similar with respect to all factors except for birth weight (which was higher for male fetuses) and for cephalic index (a higher proportion of male fetuses had a cephalic index of > 0.8) (Table 2).

Table 2. Demographic and obstetric characteristics of the study population
CharacteristicMale fetusesFemale fetusesP
  1. Data are presented as mean ± SD, n (%) or median (range). Comparison of the two groups was performed using Student's t-test for normally distributed continuous variables, the Mann–Whitney U-test for non-normally distributed continuous variables (gestational age at delivery and interval between sonographic evaluation and delivery) and the chi-square test for categorical data. N/A, not applicable.

Fetuses that met the inclusion criteria1954 (53.2)1718 (46.8)N/A
Maternal age (years)30.3 ± 5.130.6 ± 5.10.16
Nulliparous836 (42.8)692 (40.3)0.12
Gestational age at delivery (weeks)39 (24–42)39 (25–42)0.62
Delivery at < 37 weeks338 (17.3)283 (16.5)0.51
Breech presentation103 (5.4)98 (5.8)0.56
Time from fetal weight estimation to delivery (days)1 (0–3)1 (0.3)0.58
Fetal weight estimated:   
 On day of delivery546 (27.9)450 (26.2)0.23
 1 day prior to delivery742 (38.0)681 (39.6)0.30
 2 days prior to delivery391 (20.0)356 (20.7)0.59
 3 days prior to delivery275 (14.1)231 (13.4)0.58
Birth weight (g)3370 (2812–3751)3167 (2653–3585)< 0.001
Cephalic index79.9 ± 29.578.8 ± 18.90.19
 < 75226 (11.6)227 (13.3)0.13
 75–801036 (53.3)989 (58.0)0.004
 > 80683 (35.1)488 (28.6)< 0.001

Systematic error

The measures of accuracy for the different models in male and female fetuses are presented in Table 3. Most models were associated with overestimation of fetal weight, as reflected by the positive systematic error, and Model 7 (AC-FL-HC) was the only model for which the systematic error for male fetuses was not significantly different from zero (Table 3). In seven of the eight models tested, the systematic error was significantly lower for male fetuses compared with female fetuses (−0.2 to 2.1% vs. 1.3 to 6%; P < 0.001).

Table 3. Comparison of the accuracy of fetal weight estimations in male vs. female fetuses
 Correlation with birth weightSystematic error (%, mean (95% CI))Random error (%)EFW within 10% of birth weight (% (95% CI))
ModelMFPMFPMFPMFP
  • *

    Systematic error not significantly different from zero.

  • AC, abdominal circumference; BPD, biparietal diameter; EFW, estimated fetal weight; F, female fetuses; FL, femur diaphysis length; HC, head circumference; M, male fetuses.

1 (FL)0.8560.8420.130.66.0< 0.00112.813.60.00459.453.80.001
    (0.1–1.2)(5.3–6.6)    (58.3–60.5)(52.6–55.0) 
2 (AC)0.9290.9300.821.54.6< 0.0019.59.60.8774.769.5< 0.001
    (1.1–1.9)(4.1–5.0)    (73.7–75.7)(68.4–70.6) 
3 (AC-FL)0.9390.9391.001.54.8< 0.0018.68.80.3378.372.4< 0.001
    (1.1–1.9)(4.4–5.2)    (77.3–79.3)(71.3–73.5) 
4 (AC-BPD)0.9370.9380.802.13.5< 0.0018.98.90.9476.875.80.53
    (1.7–2.5)(3.1–4.0)    (75.8–77.8)(74.7–76.9) 
5 (AC-HC)0.9340.9341.00− 1.20.4< 0.0018.78.60.4476.979.60.05
    (−1.6 to − 0.8)(0.0–0.8)    (75.9–77.9)(78.6–80.6) 
6 (AC-FL-BPD)0.9440.9441.001.53.9< 0.0018.38.40.6380.576.50.003
    (1.1–1.9)(3.5–4.3)    (79.6–81.4)(75.4–77.6) 
7 (AC-FL-HC)0.9430.9431.00− 0.2*1.3< 0.0018.18.20.5281.681.00.61
    (−0.6 to 1.4)(0.9–1.7)    (80.7–82.5)(80.0–82.0) 
8 (AC-FL-BPD-HC)0.9440.9441.000.42.7< 0.0018.28.20.9381.380.40.48
    (0.1–0.8)(2.3–3.1)    (80.4–82.2)(79.4–81.4) 

We next sought to determine which of the four biometric parameters contributed most to these sex-related differences. For female fetuses, the systematic error was highest in the model that was based on FL as a single measure (Model 1; 6.0%), followed by the models that were based on AC or AC-FL (Models 2 and 3; 4.6–4.8%). In contrast, the systematic error for female fetuses was lowest in the models that incorporated HC (Models 5, 7 and 8; 0.4–2.7%), and the model based on AC-HC (Model 5) was the only model for which the systematic error was actually higher among male fetuses compared with female fetuses (−1.2% vs. 0.4%; P < 0.001).

Other measures of accuracy

The random error was similar for all models (8.1–9.6%) and was unrelated to fetal sex (Table 3). The only exception was the model based on FL as a single measure (Model 1) which resulted in a relatively large random error that was significantly higher for female fetuses compared with male fetuses (13.6% vs. 12.8%; P = 0.004).

The proportion of weight estimation within 10% of actual birth weight was higher for male fetuses in four of the eight models, three of which were based only on AC and/or FL. For three other models (4, 7 and 8), the proportion of weight estimation within 10% was similar for male and female fetuses (Table 3). Model 5 (AC-HC) was the only model for which the proportion of weight estimations within 10% was higher for female fetuses, and this difference reached borderline significance (P = 0.05).

The correlation between estimated and actual weight varied between 0.842 and 0.944 and was unrelated to fetal sex (Table 3). The correlation was higher for models that are based on three or four biometric parameters (0.943–0.944) compared with models that are based on one or two parameters (0.842–0.939), although these differences reached statistical significance only in comparison with Models 1 (FL; P < 0.001), 2 (AC; P < 0.001) and 5 (AC-HC; P = 0.02).

Effect of birth weight

In order to determine whether the sex-related differences in the accuracy of weight estimation are the result of differences in birth weight between male and female fetuses, we stratified the sex-related differences in the accuracy of weight estimation by birth weight and gestational age at delivery (shown for Model 6 in Figure 1, Table 1). The systematic error was found to be higher for female fetuses compared with male fetuses throughout the range of birth weight categories and gestational age at delivery (Figure 1) except for Model 5.

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Figure 1. Systematic error in male fetuses vs. female fetuses stratified by birth weight (a) and gestational week at delivery (b). The systematic error is presented for female (red line and red plus sign) and male (blue line and blue dots) fetuses. Positive values represent overestimation and negative values underestimation of actual birth weight. The results represent the systematic error based on the fetal weight estimated by Model 6 (AC-FL-BPD), which was selected as a representative model for the purpose of this analysis. Analyses using the other models (excluding Model 5) produced almost identical results (data not shown). The systematic error for male and female fetuses was compared using Student's t-test for each birth weight category (< 1500 g, n = 58 male fetuses and n = 46 female fetuses; 1500–2500 g, n = 260 male fetuses and n = 305 female fetuses; 2500–3000 g, n = 305 male fetuses and n = 352 female fetuses; 3000–3500 g, n = 519 male fetuses and n = 491 female fetuses; 3500–4000 g, n = 569 male fetuses and n = 397 female fetuses; and > 4000 g, n = 243 male fetuses and n = 126 female fetuses) and for each gestational age group (< 32 weeks, n = 57 male fetuses and n = 35 female fetuses; 32–34 weeks, n = 86 male fetuses and n = 83 female fetuses; 34–37 weeks, n = 195 male fetuses and n = 164 female fetuses; 37–40 weeks, n = 750 male fetuses and n = 694 female fetuses; and 40–42 weeks, n = 866 male fetuses and n = 742 female fetuses). AC, abdominal circumference; BPD, biparietal diameter; BW, birth weight; EFW, estimated fetal weight; FL, femur diaphysis length.

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Fetal sex and accuracy of weight estimation: multivariate analysis

Multivariate logistic regression analysis was performed in order to determine whether the association of fetal sex with the accuracy of sonographic weight estimation is independent of the effect of potential confounders, using the proportion of weight-estimations within 10% of actual birth weight as the dependent variable (shown for Model 6 in Table 4). Fetal sex was found to be the strongest predictor of accurate sonographic estimation, so the likelihood of a weight estimation within 10% of birth weight was 30% higher for male fetuses compared with female fetuses. A lower birth weight and a cephalic index of > 80 were found to decrease the likelihood of a weight estimation to be within 10% of the actual birth weight (Table 4).

Table 4. Effect of fetal sex on the accuracy of sonographic weight estimation: multivariate analysis
FactorLikelihood of EFW to be within ± 10% of actual birth weight* (odds ratio (95% CI))
  • Values reflect the results of multivariate logistic regression analysis.

  • *

    Based on the fetal weight estimated by Model 6 (AC-FL-BPD), which was selected as a representative model for the purpose of this analysis.

  • Significant factors.

  • Analyses using the other models (excluding Model 5) produced almost identical results (data not shown).

  • Using cephalic index < 75 as reference.

  • §

    Using interval = 0 days as reference. AC, abdominal circumference; BPD, biparietal diameter; FL, femur diaphysis length.

Male fetus1.3 (1.1–1.5)
Birth weight1.1 (1.0–1.2)
Cephalic index > 800.7 (0.6–0.8)
Cephalic index 75–800.9 (0.7–1.2)
Nulliparity0.8 (0.7–1.1)
Gestational age1.0 (0.9–1.1)
Maternal age1.02 (0.96–1.1)
Breech presentation1.2 (0.8–1.8)
Time interval between sonographic weight estimation and delivery§ 
 1 day0.9 (0.8–1.3)
 2 days1.0 (0.8–1.1)
 3 days0.9 (0.8–1.2)

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. REFERENCES

Our study has several key findings. First, for most models, the systematic error of the estimation of fetal weight was significantly lower for male fetuses than for female fetuses. Second, this finding was independent of the effects of potential confounders (including birth weight, cephalic index, parity, gestational age, maternal age, presentation, and the time interval between sonographic weight estimation and delivery). Third, it appears that the biometric parameters which contribute most to these sex-related differences are FL and AC, while models that include HC are associated with the lowest differences in the systematic error between male and female fetuses. Finally, the random error (a measure of precision rather than of accuracy) and correlation between estimated weight and birth weight are not affected by fetal sex.

There are significant differences in the intrauterine growth pattern between male and female fetuses3, 4. In addition, male and female fetuses have been shown to differ in body composition and in percentage of body fat24, and in the ratios between the various biometric parameters25. These differences may cause a given sonographic model to be associated with different degrees of accuracy for male and female fetuses. Nevertheless, this assumption has been tested in only a small number of studies. Heer et al.11, in a study of 820 singleton pregnancies, found no differences in the accuracy of the Hadlock equation (AC-FL-BPD; Model 6 in the current study) between male and female fetuses. However, their study included fetal weight estimations performed within the 14 days prior to delivery, a considerable period of time during which significant fetal growth may occur. This limitation probably accounts for the large systematic error in their study (9.4% for male fetuses and 9.0% for female fetuses, compared with 1.5% and 3.9%, respectively, in the current study (Table 3), which may mask any smaller sex-related differences in the systematic error. In contrast, in the current study, by using a large cohort of unselected women who underwent sonographic evaluation in a single tertiary center within 3 days prior to delivery, we were able to confirm our hypothesis and to demonstrate that the systematic error is consistently higher among female fetuses compared with male fetuses, even when different sonographic models are employed.

The reason for the persistently higher systematic error among female fetuses is unclear. One possible explanation is a systematic difference in the accuracy of the sonographic measurement of the different biometric parameters between male and female fetuses. Indeed, in a previous study in which we evaluated the accuracy of the sonographic measurement of HC, we found that the sonographic measurement of HC in female fetuses was significantly more similar to the actual postpartum HC measurement than for male fetuses26. A second explanation is that the regression models evaluated in the current study are associated with a more optimal fit to the actual birth weight of male fetuses compared with female fetuses. This preferential fit towards male fetuses may be explained as follows. First, there was a larger proportion of male fetuses compared with female fetuses in the cohort used to generate these regression models. Unfortunately, in the original papers of Hadlock et al.6, 7 and Warsof et al.8, no information is provided regarding the sex of the fetuses from which these models were derived. Second, there was a more significant influence of the male subgroup (compared with the female subgroup) in the cohorts from which the regression models were derived on the regression equation. Lastly, there were differences between the populations in the cohorts of our study and those from which the regression models were generated. For example, if the mean birth weight was lower in our population, then the regression models will fit better with the male fetuses in our cohort which, because of the higher birth weight in male infants compared with female infants, are more similar to the original cohort from which the regression models were derived.

We have found that the biometric parameters that contributed most to the sex-related differences in the accuracy of sonographic weight estimate were AC and FL. The reason for these findings is not clear but it may be a reflection of the selective differences in intrauterine growth patterns, between male and female fetuses, of the anatomic structures on which these parameters are based3, 25. Models that incorporate HC have been previously shown to be more accurate than models which are based on BPD, independently of fetal sex27. Considering the differences in the cephalic index between male and female fetuses in the current study, it is not surprising that sex-related differences in the accuracy of weight estimation were lower for models that incorporated HC (a measure that is independent of cephalic index) compared with models that are based on BPD.

In conclusion, there appear to be significant differences in the accuracy of sonographic weight estimation between male and female fetuses, and these differences are independent of other variables that are also related to fetal gender, such as birth weight and cephalic index. This information may provide support to the development of sex-specific sonographic models for fetal weight estimation, and such sex-specific models may be of importance, especially in cases in which fetal growth abnormality is suspected, as the integration of fetal sex may decrease the rate of false-negative or false-positive prediction of fetal growth abnormality. Indeed, Schild et al.28–30 have reported that the use of such a sex-specific model is more accurate than other widely accepted models. One issue that should be emphasized is that although the sex-related differences in the systematic error were statistically significant (as a result of the large sample size), the absolute magnitude of these differences was relatively small and the clinical significance of these differences is uncertain. Nevertheless, the development of sex-specific models may be one step towards the development of customized models that include corrections for additional factors which affect the accuracy of weight estimation and that may be associated with an even greater improvement in the accuracy of weight estimation. More studies are needed in order to provide a better understanding of the reasons for these sex-related differences and to determine whether the use of sex-specific models may improve the accuracy of sonographic weight estimation in male and female fetuses.

REFERENCES

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. REFERENCES