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Protocol
Postnatal gestational age estimation using newborn screening blood spots: a proposed validation protocol
  1. Malia S Q Murphy1,
  2. Steven Hawken1,
  3. Katherine M Atkinson1,
  4. Jennifer Milburn2,
  5. Jesmin Pervin3,
  6. Courtney Gravett4,
  7. Jeffrey S A Stringer5,
  8. Anisur Rahman6,
  9. Eve Lackritz4,
  10. Pranesh Chakraborty2,
  11. Kumanan Wilson1
  1. 1 Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
  2. 2 Newborn Screening Ontario, Children’s Hospital of Eastern Ontario, Ottawa, Canada
  3. 3 Maternal and Child Health Division, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh
  4. 4 Global Alliance to Prevent Prematurity and Stillbirth, Seattle, USA
  5. 5 Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, USA
  6. 6 Matlab Health Research Centre, International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh
  1. Correspondence to Kumanan Wilson; kwilson{at}ohri.ca

Abstract

Background Knowledge of gestational age (GA) is critical for guiding neonatal care and quantifying regional burdens of preterm birth. In settings where access to ultrasound dating is limited, postnatal estimates are frequently used despite the issues of accuracy associated with postnatal approaches. Newborn metabolic profiles are known to vary by severity of preterm birth. Recent work by our group and others has highlighted the accuracy of postnatal GA estimation algorithms derived from routinely collected newborn screening profiles. This protocol outlines the validation of a GA model originally developed in a North American cohort among international newborn cohorts.

Methods Our primary objective is to use blood spot samples collected from infants born in Zambia and Bangladesh to evaluate our algorithm’s capacity to correctly classify GA within 1, 2, 3 and 4 weeks. Secondary objectives are to 1) determine the algorithm's accuracy in small-for-gestational-age and large-for-gestational-age infants, 2) determine its ability to correctly discriminate GA of newborns across dichotomous thresholds of preterm birth (≤34 weeks, <37 weeks GA) and 3) compare the relative performance of algorithms derived from newborn screening panels including all available analytes and those restricted to analyte subsets. The study population will consist of infants born to mothers already enrolled in one of two preterm birth cohorts in Lusaka, Zambia, and Matlab, Bangladesh. Dried blood spot samples will be collected and sent for analysis in Ontario, Canada, for model validation.

Discussion This study will determine the validity of a GA estimation algorithm across ethnically diverse infant populations and assess population specific variations in newborn metabolic profiles.

  • gestational age
  • validation study
  • metabolomics
  • newborn screening
  • screening
  • obstetrics
  • epidemiology

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

https://doi.org/10.1136/bmjgh-2017-000365

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    Footnotes

    • Contributors The protocol manuscript was developed by MSQM, KW and SH. KW, MSQM, KMA and SH designed the study with contributions from PC, JM, EL, CG, AR, JP and JSAS. All authors contributed to editing of the manuscript.

    • Funding This project is funded by the Bill & Melinda Gates Foundation, Seattle, Washington (OPP1141535).

    • Competing interests None declared.

    • Ethics approval Ottawa Hospital Health Science Network; Children's Hospital of Eastern Ontario Research Ethics Board; University of Zambia Biomedical Research Ethics Committee; icddr,b Ethical Review Committee.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data sharing statement The data that will support the findings of this study will be available from the corresponding author on reasonable request.