Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada.
Department of Epidemiology and Community Health, University of Ottawa, Ottawa, Canada.
Elife. 2019 Mar 19;8:e42627. doi: 10.7554/eLife.42627.
This study sought to evaluate the performance of metabolic gestational age estimation models developed in Ontario, Canada in infants born in Bangladesh. Cord and heel prick blood spots were collected in Bangladesh and analyzed at a newborn screening facility in Ottawa, Canada. Algorithm-derived estimates of gestational age and preterm birth were compared to ultrasound-validated estimates. 1036 cord blood and 487 heel prick samples were collected from 1069 unique newborns. The majority of samples (93.2% of heel prick and 89.9% of cord blood) were collected from term infants. When applied to heel prick data, algorithms correctly estimated gestational age to within an average deviation of 1 week overall (root mean square error = 1.07 weeks). Metabolic gestational age estimation provides accurate population-level estimates of gestational age in this data set. Models were effective on data obtained from both heel prick and cord blood, the latter being a more feasible option in low-resource settings.
本研究旨在评估在加拿大安大略省开发的代谢性胎龄估计模型在孟加拉国出生的婴儿中的表现。在孟加拉国采集脐带血和足跟血斑，并在加拿大渥太华的新生儿筛查机构进行分析。将算法衍生的胎龄和早产估计值与超声验证的估计值进行比较。从 1069 名新生儿中采集了 1036 份脐带血和 487 份足跟血样本。大多数样本（足跟血的 93.2%和脐带血的 89.9%）来自足月婴儿。当应用于足跟血数据时，算法总体上正确估计胎龄的平均偏差为 1 周（均方根误差=1.07 周）。代谢性胎龄估计为该数据集提供了准确的人群胎龄估计。这些模型在足跟血和脐血数据上都有效，后者在资源匮乏的环境中是一种更可行的选择。
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