Rizzo Giuseppe, Prefumo Federico, Ferrazzi Enrico, Zanardini Cristina, Di Martino Daniela, Boito Simona, Aiello Elisa, Ghi Tullio
a Department of Obstetrics and Gynecology , Università Roma Tor Vergata , Roma , Italy .
b Department of Obstetrics and Gynecology , Università of Brescia , Italy .
J Matern Fetal Neonatal Med. 2016 Dec;29(23):3768-75. doi: 10.3109/14767058.2016.1149565. Epub 2016 Mar 3.
To evaluate the effect of fetal sex on singleton pregnancy growth charts customized for parental characteristics, race, and parity Methods: In a multicentric cross-sectional study, 8070 ultrasonographic examinations from low-risk singleton pregnancies between 16 and 40 weeks of gestation were considered. The fetal measurements obtained were biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), and femur length (FL). Quantile regression was used to examine the impact of fetal sex across the biometric percentiles of the fetal measurements considered together with parents' height, weight, parity, and race.
Fetal gender resulted to be a significant covariate for BDP, HC, and AC with higher values for male fetuses (p ≤ 0.0009). Minimal differences were found among sexes for FL. Parity, maternal race, paternal height and maternal height, and weight resulted significantly related to the fetal biometric parameters considered independently from fetal gender.
In this study, we constructed customized biometric growth charts for fetal sex, parental, and obstetrical characteristics using quantile regression. The use of gender-specific charts offers the advantage to define individualized normal ranges of fetal biometric parameters at each specific centile. This approach may improve the antenatal identification of abnormal fetal growth.
评估胎儿性别对根据父母特征、种族和胎次定制的单胎妊娠生长曲线的影响。方法:在一项多中心横断面研究中,纳入了妊娠16至40周的低风险单胎妊娠的8070次超声检查。获取的胎儿测量指标包括双顶径(BPD)、头围(HC)、腹围(AC)和股骨长度(FL)。使用分位数回归来研究胎儿性别对与父母身高、体重、胎次和种族一起考虑的胎儿测量生物统计学百分位数的影响。
胎儿性别是双顶径、头围和腹围的显著协变量,男胎的值更高(p≤0.0009)。股骨长度在不同性别之间差异极小。胎次、母亲种族、父亲身高和母亲身高及体重与独立于胎儿性别的胎儿生物统计学参数显著相关。
在本研究中,我们使用分位数回归构建了针对胎儿性别、父母和产科特征的定制生物统计学生长曲线。使用特定性别的曲线具有在每个特定百分位数定义胎儿生物统计学参数个体化正常范围的优势。这种方法可能会改善产前对异常胎儿生长的识别。