Percent error of ultrasound examination to estimate fetal weight at term in different categories of birth weight with focus on maternal diabetes and obesity

超声检查估算足月胎儿体重的误差百分比,针对不同出生体重类别,重点关注孕妇糖尿病和肥胖。

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Abstract

BACKGROUND: Sonography based estimate of fetal weight is a considerable issue for delivery planning. The study evaluated the influence of diabetes, obesity, excess weight gain, fetal and neonatal anthropometrics on accuracy of estimated fetal weight with respect to the extent of the percent error of estimated fetal weight to birth weight for different categories. METHODS: Multicenter retrospective analysis from 11,049 term deliveries and fetal ultrasound biometry performed within 14 days to delivery. Estimated fetal weight was calculated by Hadlock IV. Percent error from birth weight was determined for categories in 250 g increments between 2500 g and 4500 g. Estimated fetal weight accuracy was categorized as accurate ≤ 10% of birth weight, under- and overestimated by >  ± 10% - ± 20% and > 20%. RESULTS: Diabetes was diagnosed in 12.5%, obesity in 12.6% and weight gain exceeding IOM recommendation in 49.1% of the women. The percentage of accurate estimated fetal weight was not significantly different in the presence of maternal diabetes (70.0% vs. 71.8%, p = 0.17), obesity (69.6% vs. 71.9%, p = 0.08) or excess weight gain (71.2% vs. 72%, p = 0.352) but of preexisting diabetes (61.1% vs. 71.7%; p = 0.007) that was associated with the highest macrosomia rate (26.9%). Mean percent error of estimated fetal weight from birth weight was 2.39% ± 9.13%. The extent of percent error varied with birth weight with the lowest numbers for 3000 g-3249 g and increasing with the extent of birth weight variation: 5% ± 11% overestimation in the lowest and 12% ± 8% underestimation in the highest ranges. CONCLUSION: Diabetes, obesity and excess weight gain are not necessarily confounders of estimated fetal weight accuracy. Percent error of estimated fetal weight is closely related to birth weight with clinically relevant over- and underestimation at both extremes. This work provides detailed data regarding the extent of percent error for different birth weight categories and may therefore improve delivery planning.

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