{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T14:27:51Z","timestamp":1785940071120,"version":"3.56.0"},"update-to":[{"DOI":"10.12688\/gatesopenres.13155.1","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2021,1,28]],"date-time":"2021-01-28T00:00:00Z","timestamp":1611792000000}}],"reference-count":21,"publisher":"F1000 Research Ltd","license":[{"start":{"date-parts":[[2021,1,28]],"date-time":"2021-01-28T00:00:00Z","timestamp":1611792000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000865","name":"Bill and Melinda Gates Foundation","doi-asserted-by":"publisher","award":["OPP1182996"],"award-info":[{"award-number":["OPP1182996"]}],"id":[{"id":"10.13039\/100000865","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000865","name":"Bill and Melinda Gates Foundation","doi-asserted-by":"publisher","award":["OPP1184574"],"award-info":[{"award-number":["OPP1184574"]}],"id":[{"id":"10.13039\/100000865","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["gatesopenresearch.org"],"crossmark-restriction":false},"short-container-title":["Gates Open Res"],"abstract":"<ns3:p>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\u2019s 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\u2019s 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.<\/ns3:p>","DOI":"10.12688\/gatesopenres.13155.2","type":"journal-article","created":{"date-parts":[[2021,1,28]],"date-time":"2021-01-28T15:59:30Z","timestamp":1611849570000},"page":"150","update-policy":"https:\/\/doi.org\/10.12688\/gatesopenres.crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Metabolic gestational age assessment in low resource settings: a validation protocol"],"prefix":"10.12688","volume":"4","author":[{"given":"A. 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A.","family":"Stringer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Humphrey","family":"Mwape","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joan T.","family":"Price","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1615-3856","authenticated-orcid":false,"given":"Hilda Angela","family":"Mujuru","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7280-3801","authenticated-orcid":false,"given":"Gwendoline","family":"Chimhini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thulani","family":"Magwali","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Louisa","family":"Mudawarima","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pranesh","family":"Chakraborty","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7522-5824","authenticated-orcid":false,"given":"Gary L.","family":"Darmstadt","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1741-7705","authenticated-orcid":false,"given":"Kumanan","family":"Wilson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2560","published-online":{"date-parts":[[2021,1,28]]},"reference":[{"key":"ref-1","doi-asserted-by":"publisher","first-page":"e20153303","DOI":"10.1542\/peds.2015-3303","article-title":"Validity of Newborn Clinical Assessment to Determine Gestational Age in Bangladesh.","volume":"138","author":"A Lee","year":"2016","journal-title":"Pediatrics."},{"key":"ref-2","doi-asserted-by":"publisher","first-page":"6047-56","DOI":"10.1016\/j.vaccine.2016.03.045","article-title":"Preterm birth: Case definition & guidelines for data collection, analysis, and presentation of immunisation safety data.","volume":"34","author":"J Quinn","year":"2016","journal-title":"Vaccine."},{"key":"ref-3","doi-asserted-by":"publisher","first-page":"290-8","DOI":"10.1111\/j.1365-3016.2006.00741.x","article-title":"Last menstrual period provides the best estimate of gestation length for women in rural Guatemala.","volume":"20","author":"L Neufeld","year":"2006","journal-title":"Paediatr Perinat Epidemiol."},{"key":"ref-4","doi-asserted-by":"publisher","first-page":"367-73","DOI":"10.1038\/pr.2013.212","article-title":"Metabolomics of prematurity: analysis of patterns of amino acids, enzymes, and endocrine markers by categories of gestational age.","volume":"75","author":"K Wilson","year":"2014","journal-title":"Pediatr Res."},{"key":"ref-5","doi-asserted-by":"publisher","first-page":"511.e1-511.e13","DOI":"10.1016\/j.ajog.2015.11.029","article-title":"Gestational dating by metabolic profile at birth: a California cohort study.","volume":"214","author":"L Jelliffe-Pawlowski","year":"2016","journal-title":"Am J Obstet Gynecol."},{"key":"ref-6","doi-asserted-by":"publisher","first-page":"e42627","DOI":"10.7554\/eLife.42627","article-title":"External validation of postnatal gestational age estimation using newborn metabolic profiles in Matlab, Bangladesh.","volume":"8","author":"M Murphy","year":"2019","journal-title":"eLife."},{"key":"ref-7","doi-asserted-by":"publisher","DOI":"10.1101\/2020.07.21.20158196","article-title":"Title: Development and external validation of machine learning algorithms for postnatal gestational age estimation using clinical data and metabolomic markers.","author":"S Hawken","year":"2020","journal-title":"MedRxiv."},{"key":"ref-8","doi-asserted-by":"publisher","first-page":"25","DOI":"10.12688\/gatesopenres.12820.3","article-title":"The Zambian Preterm Birth Prevention Study (ZAPPS): Cohort characteristics at enrollment [version 3; 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Slusher, Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA, 02 Nov 2020, version 1, indexed","URL":"https:\/\/gatesopenresearch.org\/articles\/4-150\/v1#referee-response-29735","order":0,"name":"referee-response-29735","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Kumanan Wilson<\/b>; \n<i>Posted: 10 Nov 2020<\/i>; Thank you for your review of our article.  We agree with the reviewer that \n<i>exceedingly <\/i>should be removed from the manuscript, and we will do this. The definition of a rare disease varies by country (i.e. US &lt;200,000, Europe, &lt;5 in 10,000). The prevalence of hemoglobinopathies are much higher in African then the rest of the world (10.74 vs. 2.73 per 1000) (Fattoum, Mediter J of Hematol and Infect Dis, 2009).  We have conducted a cost effectiveness analysis (Colyle et al, under review) of our previous study in Bangladesh (Murphy et al, eLife, 2019). This paper is currently under review, and we will add details to the discussion when it is published. There are a number of things to consider when considering different options for preterm birth surveillance including cost and health outcomes. Ultimately the decision about whether to undertake such an initiative will be up to policy makers and global funders. Implementation studies such as this will inform governments and global health funders into the usefulness of these initiatives.  G6PDH is not on the disease panel in Ontario, which is why it was not included in this study.","URL":"https:\/\/gatesopenresearch.org\/articles\/4-150\/v2#referee-comment-3383","order":1,"name":"referee-comment-3383","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.21956\/gatesopenres.14350.r30047, Thokozile Rosemary Malaba, Division of Epidemiology & Biostatistics, School of Public Health & Family Medicine, University of Cape Town, Cape Town, South Africa, 11 Jan 2021, version 1, indexed","URL":"https:\/\/gatesopenresearch.org\/articles\/4-150\/v1#referee-response-30047","order":2,"name":"referee-response-30047","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"<b>Kumanan Wilson<\/b>; \n<i>Posted: 19 Jan 2021<\/i>; This is a well-written manuscript and I only have the following minor comments\/queries:  \n<b>Background:<\/b>  Repetition of the following paragraph: \u201cwhile our previous work, and that of others, suggests potential value\u2026widely as a surveillance took for preterm birth&quot;.  \n<b><i>Response:<\/i><\/b> Thank you for noticing the paragraph repetition, it appears to be an error during publication.  \n<b>Methods:<\/b>  Perhaps the authors could provide the target sample sizes for samples from each site - the justification\/calculations for each site are not clear.  \n<b><i>Response: <\/i><\/b> \n<i>We have added a subsection to the methods providing further details on the sample size calculations. The estimated sample size provided for each site is the target sample size for each population. For sample size requirements for an external validation, we followed the general philosophy and guidance of Steyerburg\u2019s&nbsp;Clinical Prediction Models.&nbsp;The estimated preterm birth rates at each site and number of ultrasounds that could&nbsp;reasonably&nbsp;be obtained were also considered. We were guided by a&nbsp;pragmatic&nbsp;target sample size of 20 observations in the smallest subgroup as this sample size is sufficient to calculate a robust summary&nbsp;(e.g. mean and CI)&nbsp;of the reported performance metrics&nbsp;in each subgroup of interest, for continuous GA, without requiring an unachievably large sample size.&nbsp;For example, if the rate of &lt;34 weeks was 5%, this would require an overall sample size of n=400 (20\/0.05) for that site. &nbsp;  This subsection is presented following the site selection section in the Methods.<\/i>  Could there be standardization&nbsp;of language\/structure of the site descriptions in terms of the&nbsp;site (which facilities), site\u2019s PTB rate, timing of enrolment, eligibility\/inclusion criteria, sample size of samples vs participants?  \n<b><i>Response:<\/i><\/b> W\n<i>e have structured the information, so it follows a similar pattern for each site \u2013 site details, estimated PTB, enrollment details, target sample size.&nbsp; &nbsp;<\/i>  Site-specific comments:  Bangladesh  \n<i>\u201c...Kumudini Hospital, and half will be enrolled at 20 weeks gestation.....to allow for first trimester ultrasound validation<\/i>\u201d  Were these women enrolled&nbsp;\n<b>at 20 weeks&nbsp;<\/b>or at&nbsp;\n<b>20 weeks or earlier<\/b>&nbsp;- if the former perhaps first trimester ultrasound should be changed to early ultrasound.        \n<b><i>Response:<\/i><\/b> \n<i>Thank you, we have edited this to say \u2018enrolled at or before 20 weeks to allow for early ultrasound validation.<\/i>    Kenya  \n<i>\u201cParticipants enrolled at their first ANC visit....\u201d<\/i>  \n<i>Were women enrolled at this visit enrolled regardless of gestational age?<\/i>  \n<i>Linked to point above \u201cWomen are typically enrolled prior to 20 weeks gestation\u201d - what is the procedure for late presenters? Are they enrolled? If yes do they have an ultrasound assessment?<\/i>          \n<b><i>Response:<\/i><\/b> \n<i>At this site, participants are typically enrolled prior to 20 weeks. Some participants are enrolled outside of the recommended range. All participants enrolled undergo ultrasound, and the date of ultrasound will be considered during analysis.<\/i>    Zimbabwe  Similar to the comment above are there any GA restrictions for women enrolled at first ANC visit?      \n<b><i>Response:<\/i><\/b> \n<i>Ultrasound enrollment target is &lt;20 weeks, however enrollment beyond this gestational age may occur if this is necessary to achieve sample size goals. This would be accounted for in the analysis.<\/i>      \u201cYielding a total sample size of approximately 1000 participants\u201d.  Does this mean the goal sample size is estimated to be 1000 heel and cord samples?        \n<b><i>Response:<\/i><\/b> \n<i>We have updated this to add \u2018\u2026with 1000 heel and 500 cord samples &nbsp;<\/i>  \n<i>\u201cClassification of preterm birth, as well as SGA\/AGA\/LGA\u2026.\u201d<\/i>  Which standards will be used for classification of size for gestation age - is it an international standard like INTERGROWTH-21st or regional standards?    \n<b><i>Response:<\/i><\/b> \n<i>We will use intergrowth-21 standards for gestational age classification, we have added this to the statistical analysis section.<\/i>","URL":"https:\/\/gatesopenresearch.org\/articles\/4-150\/v2#referee-comment-3398","order":3,"name":"referee-comment-3398","label":"Referee Comment","group":{"name":"article-reports","label":"Article Reports"}},{"value":"10.21956\/gatesopenres.14350.r30180, Zilma Silveira Nogueira Reis, Center of Health Informatics, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil, 22 Jan 2021, version 1, indexed","URL":"https:\/\/gatesopenresearch.org\/articles\/4-150\/v1#referee-response-30180","order":4,"name":"referee-response-30180","label":"Referee Report","group":{"name":"article-reports","label":"Article Reports"}},{"value":"This work was supported by the Bill and Melinda Gates Foundation [OPP1184574 (KW) and OPP1182996 (GLD)]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.","order":5,"name":"grant-information","label":"Grant Information"},{"value":"This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","order":0,"name":"copyright-info","label":"Copyright"}]}}