Bota A Brianne, Ward Victoria, Hawken Stephen, Wilson Lindsay A, Lamoureux Monica, Ducharme Robin, Murphy Malia S Q, Denize Kathryn M, Henderson Matthew, Saha Samir K, Akther Salma, Otieno Nancy A, Munga Stephen, Atito Raphael O, Stringer Jeffrey S A, Mwape Humphrey, Price Joan T, Mujuru Hilda Angela, Chimhini Gwendoline, Magwali Thulani, Mudawarima Louisa, Chakraborty Pranesh, Darmstadt Gary L, Wilson Kumanan
Clinical Epidemiology Program, Ottawa Health Research Institute, Ottawa, ON, Canada.
Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, USA.
Gates Open Res. 2021 Jan 28;4:150. doi: 10.12688/gatesopenres.13155.2. eCollection 2020.
Preterm birth is the leading global cause of neonatal morbidity and mortality. Reliable gestational age estimates are useful for quantifying population burdens of preterm birth and informing allocation of resources to address the problem. However, evaluating gestational age in low-resource settings can be challenging, particularly in places where access to ultrasound is limited. Our group has developed an algorithm using newborn screening analyte values derived from dried blood spots from newborns born in Ontario, Canada for estimating gestational age within one to two weeks. The primary objective of this study is to validate a program that derives gestational age estimates from dried blood spot samples (heel-prick or cord blood) collected from health and demographic surveillance sites and population representative health facilities in low-resource settings in Zambia, Kenya, Bangladesh and Zimbabwe. We will also pilot the use of an algorithm to identify birth percentiles based on gestational age estimates and weight to identify small for gestational age infants. Once collected from local sites, samples will be tested by the Newborn Screening Ontario laboratory at the Children's Hospital of Eastern Ontario (CHEO) in Ottawa, Canada. Analyte values will be obtained through laboratory analysis for estimation of gestational age as well as screening for other diseases routinely conducted at Ontario's newborn screening program. For select conditions, abnormal screening results will be reported back to the sites in real time to facilitate counseling and future clinical management. We will determine the accuracy of our existing algorithm for estimation of gestational age in these newborn samples. Results from this research hold the potential to create a feasible method to assess gestational age at birth in low- and middle-income countries where reliable estimation may be otherwise unavailable.
早产是全球新生儿发病和死亡的主要原因。可靠的孕周估计对于量化早产的人群负担以及为解决该问题的资源分配提供依据很有用。然而，在资源匮乏地区评估孕周可能具有挑战性，尤其是在超声检查受限的地方。我们团队开发了一种算法，利用从加拿大安大略省出生的新生儿干血斑中获得的新生儿筛查分析物值来在一到两周内估计孕周。本研究的主要目的是验证一个程序，该程序从赞比亚、肯尼亚、孟加拉国和津巴布韦等资源匮乏地区的健康和人口监测点以及具有人群代表性的卫生机构收集的干血斑样本（足跟采血或脐带血）中得出孕周估计值。我们还将试行使用一种算法，根据孕周估计值和体重来确定出生百分位数，以识别小于胎龄儿。一旦从当地收集样本，将由加拿大渥太华东安大略儿童医院（CHEO）的安大略新生儿筛查实验室进行检测。将通过实验室分析获得分析物值，以估计孕周以及进行安大略省新生儿筛查项目常规开展的其他疾病筛查。对于某些特定情况，异常筛查结果将实时反馈给各监测点，以方便咨询和未来的临床管理。我们将确定我们现有的算法在这些新生儿样本中估计孕周的准确性。这项研究的结果有可能创造一种可行的方法，用于在可靠估计可能无法实现的低收入和中等收入国家评估出生时的孕周。
