Department of Neonatology, Princess Amalia Department of Pediatrics, Isala, Zwolle, The Netherlands; Department of Neonatology, Amalia Children's Hospital, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.
Department of Clinical Epidemiology, Bioinformatics & Biostatistics, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Am J Obstet Gynecol. 2019 Apr;220(4):383.e1-383.e17. doi: 10.1016/j.ajog.2018.12.023. Epub 2018 Dec 18.
Antenatal detection of intrauterine growth restriction remains a major obstetrical challenge, with the majority of cases not detected before birth. In these infants with undetected intrauterine growth restriction, the diagnosis must be made after birth. Clinicians use birthweight charts to identify infants as small-for-gestational-age if their birthweights are below a predefined threshold for gestational age. The choice of birthweight chart strongly affects the classification of small-for-gestational-age infants and has an impact on both research findings and clinical practice. Despite extensive literature on pathological risk factors associated with small-for-gestational-age, controversy exists regarding the exclusion of affected infants from a reference population.
This study aims to identify pathological risk factors for abnormal fetal growth, to quantify their effects, and to use these findings to calculate prescriptive birthweight charts for the Dutch population.
We performed a retrospective cross-sectional study, using routinely collected data of 2,712,301 infants born in The Netherlands between 2000 and 2014. Risk factors for abnormal fetal growth were identified and categorized in 7 groups: multiple gestation, hypertensive disorders, diabetes, other pre-existing maternal medical conditions, maternal substance (ab)use, medical conditions related to the pregnancy, and congenital malformations. The effects of these risk factors on mean birthweight were assessed using linear regression. Prescriptive birthweight charts were derived from live-born singleton infants, born to ostensibly healthy mothers after uncomplicated pregnancies and spontaneous onset of labor. The Box-Cox-t distribution was used to model birthweight and to calculate sex-specific percentiles. The new charts were compared to various existing birthweight and fetal-weight charts.
We excluded 111,621 infants because of missing data on birthweight, gestational age or sex, stillbirth, or a gestational age not between 23 and 42 weeks. Of the 2,599,640 potentially eligible infants, 969,552 (37.3%) had 1 or more risk factors for abnormal fetal growth and were subsequently excluded. Large absolute differences were observed between the mean birthweights of infants with and without these risk factors, with different patterns for term and preterm infants. The final low-risk population consisted of 1,629,776 live-born singleton infants (50.9% male), from which sex-specific percentiles were calculated. Median and 10th percentiles closely approximated fetal-weight charts but consistently exceeded existing birthweight charts.
Excluding risk factors that cause lower birthweights results in prescriptive birthweight charts that are more akin to fetal-weight charts, enabling proper discrimination between normal and abnormal birthweight. This proof of concept can be applied to other populations.
产前检测宫内生长受限仍然是一个主要的产科挑战,大多数病例在出生前都没有被发现。在这些未被发现的宫内生长受限的婴儿中,出生后必须做出诊断。如果婴儿的出生体重低于针对胎龄的预定义阈值,临床医生会使用出生体重图表将其归类为小于胎龄儿。出生体重图表的选择对小于胎龄儿的分类有很大影响,并且对研究结果和临床实践都有影响。尽管有大量关于与小于胎龄儿相关的病理危险因素的文献,但关于将受影响的婴儿从参考人群中排除仍存在争议。
本研究旨在确定异常胎儿生长的病理危险因素,量化其影响,并利用这些发现为荷兰人群制定规定性的出生体重图表。
我们进行了一项回顾性的横断面研究,使用了 2712301 名 2000 年至 2014 年在荷兰出生的婴儿的常规收集数据。确定了异常胎儿生长的危险因素,并将其分为 7 组:多胎妊娠、高血压疾病、糖尿病、其他既往的母亲医疗状况、母亲物质(滥用)、与妊娠相关的医疗状况和先天性畸形。使用线性回归评估这些危险因素对平均出生体重的影响。从看似健康的母亲分娩的、无并发症妊娠和自发性临产的单胎活产婴儿中得出规定性的出生体重图表。Box-Cox-t 分布用于对出生体重进行建模并计算性别特异性百分位数。新图表与各种现有的出生体重和胎儿体重图表进行了比较。
我们排除了 111621 名婴儿,因为他们的出生体重、胎龄或性别、死产或胎龄不在 23 至 42 周之间的数据缺失。在 2599640 名有潜在资格的婴儿中,有 969552 名(37.3%)有 1 个或多个异常胎儿生长的危险因素,随后被排除在外。有和没有这些危险因素的婴儿的平均出生体重之间存在较大的绝对差异,足月和早产儿的模式不同。最终的低风险人群由 1629776 名单胎活产婴儿(50.9%为男性)组成,从中计算出性别特异性百分位数。中位数和第 10 百分位数与胎儿体重图表非常接近,但始终超过现有的出生体重图表。
排除导致较低出生体重的危险因素会导致规定性的出生体重图表更类似于胎儿体重图表,从而能够正确区分正常和异常的出生体重。这一概念验证可以应用于其他人群。