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Epidemiology
Research
Performance of a postnatal metabolic gestational age algorithm: a retrospective validation study among ethnic subgroups in Canada
  1. Steven Hawken1,2,3,
  2. Robin Ducharme3,
  3. Malia S Q Murphy1,
  4. Katherine M Atkinson1,4,
  5. Beth K Potter1,3,2,
  6. Pranesh Chakraborty5,6,
  7. Kumanan Wilson1,3,2,7
  1. 1 Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
  2. 2 School of Epidemiology, Public Health and Preventative Medicine, University of Ottawa, Ottawa, Ontario, Canada
  3. 3 uOttawa, Institute for Clinical Evaluative Sciences, Ottawa, Ontario, Canada
  4. 4 Department of Public Health Sciences, Karolinska Institute, Stockholm, Sweden
  5. 5 Department of Paediatrics, University of Ottawa, Ottawa, Ontario, Canada
  6. 6 Newborn Screening Ontario, Children’s Hospital of Eastern Ontario, Ottawa, Ontario, Canada
  7. 7 Department of Medicine, University of Ottawa, Ottawa, Ontario, Canada
  1. Correspondence to Dr Kumanan Wilson; kwilson{at}ohri.ca

Abstract

Objectives Biological modelling of routinely collected newborn screening data has emerged as a novel method for deriving postnatal gestational age estimates. Validation of published models has previously been limited to cohorts largely consisting of infants of white Caucasian ethnicity. In this study, we sought to determine the validity of a published gestational age estimation algorithm among recent immigrants to Canada, where maternal landed immigrant status was used as a surrogate measure of infant ethnicity.

Design We conducted a retrospective validation study in infants born in Ontario between April 2009 and September 2011.

Setting Provincial data from Ontario, Canada were obtained from the Institute for Clinical Evaluative Sciences.

Participants The dataset included 230 034 infants born to non-landed immigrants and 70 098 infants born to immigrant mothers. The five most common countries of maternal origin were India (n=10 038), China (n=7468), Pakistan (n=5824), The Philippines (n=5441) and Vietnam (n=1408). Maternal country of origin was obtained from Citizenship and Immigration Canada’s Landed Immigrant Database.

Primary and secondary outcome measures Performance of a postnatal gestational age algorithm was evaluated across non-immigrant and immigrant populations.

Results Root mean squared error (RMSE) of 1.05 weeks was observed for infants born to non-immigrant mothers, whereas RMSE ranged from 0.98 to 1.15 weeks among infants born to immigrant mothers. Area under the receiver operating characteristic curve for distinguishing term versus preterm infants (≥37 vs <37 weeks gestational age or >34 vs ≤34 weeks gestational age) was 0.958 and 0.986, respectively, in the non-immigrant subgroup and ranged from 0.927 to 0.964 and 0.966 to 0.99 in the immigrant subgroups.

Conclusions Algorithms for postnatal determination of gestational age may be further refined by development and validation of region or ethnicity-specific models. However, our results provide reassurance that an algorithm developed from Ontario-born infant cohorts performs well across a range of ethnicities and maternal countries of origin without modification.

  • gestational age
  • prediction modelling
  • newborn screening

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/bmjopen-2016-015615

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    Footnotes

    • Contributors SH and RD were involved in data acquisition and statistical analysis. SH, MSQM and KW drafted and edited the manuscript. KMA and MSQM provided project coordination. BKP and PC critically edited the manuscript for important intellectual content. KW was responsible for the conceptual design of the study.

    • Funding This work was supported by The Bill & Melinda Gates Foundation [OPP1141535]. It was also supported by the Institute for Clinical Evaluative Sciences (ICES), which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC).

    • Competing interests All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: the authors had financial support from The Bill & Melinda Gates Foundation for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. The opinions, results and conclusions reported in this paper are those of the authors and are independent from the funding sources. No endorsement by ICES or the Ontario MOHLTC is intended or should be inferred. Parts of this material are based on data and information compiled and provided by the Canadian Institute of Health Information (CIHI). However, the analyses, conclusions, opinions and statements expressed herein are those of the author, and not necessarily those of CIHI.

    • Ethics approval Ottawa Health Science Network Research Ethics Board.

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

    • Data sharing statement All data used in this study were obtained from the Institute for Clinical Evaluative Sciences and are accessible to individuals with appropriate authorisation.