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dc.contributor.authorAllotey, Jen_US
dc.contributor.authorSnell, KIEen_US
dc.contributor.authorChan, Cen_US
dc.contributor.authorHooper, Ren_US
dc.contributor.authorDodds, Jen_US
dc.contributor.authorRogozinska, Een_US
dc.contributor.authorKhan, KSen_US
dc.contributor.authorPoston, Len_US
dc.contributor.authorKenny, Len_US
dc.contributor.authorMyers, Jen_US
dc.contributor.authorThilaganathan, Ben_US
dc.contributor.authorChappell, Len_US
dc.contributor.authorMol, BWen_US
dc.contributor.authorVon Dadelszen, Pen_US
dc.contributor.authorAhmed, Aen_US
dc.contributor.authorGreen, Men_US
dc.contributor.authorPoon, Len_US
dc.contributor.authorKhalil, Aen_US
dc.contributor.authorMoons, KGMen_US
dc.contributor.authorRiley, RDen_US
dc.contributor.authorThangaratinam, Sen_US
dc.contributor.authorIPPIC Collaborative Networken_US
dc.date.accessioned2018-01-16T08:59:33Z
dc.date.available2017-09-19en_US
dc.date.issued2017en_US
dc.date.submitted2017-09-28T08:20:14.096Z
dc.identifier.urihttp://qmro.qmul.ac.uk/xmlui/handle/123456789/31323
dc.description.abstractBackground: Pre-eclampsia, a condition with raised blood pressure and proteinuria is associated with an increased risk of maternal and offspring mortality and morbidity. Early identification of mothers at risk is needed to target management. Methods/design: We aim to systematically review the existing literature to identify prediction models for pre-eclampsia. We have established the International Prediction of Pregnancy Complication Network (IPPIC), made up of 72 researchers from 21 countries who have carried out relevant primary studies or have access to existing registry databases, and collectively possess data from more than two million patients. We will use the individual participant data (IPD) from these studies to externally validate these existing prediction models and summarise model performance across studies using random-effects meta-analysis for any, late (after 34 weeks) and early (before 34 weeks) onset pre-eclampsia. If none of the models perform well, we will recalibrate (update), or develop and validate new prediction models using the IPD. We will assess the differential accuracy of the models in various settings and subgroups according to the risk status. We will also validate or develop prediction models based on clinical characteristics only; clinical and biochemical markers; clinical and ultrasound parameters; and clinical, biochemical and ultrasound tests. Discussion: Numerous systematic reviews with aggregate data meta-analysis have evaluated various risk factors separately or in combination for predicting pre-eclampsia, but these are affected by many limitations. Our large-scale collaborative IPD approach encourages consensus towards well developed, and validated prognostic models, rather than a number of competing non-validated ones. The large sample size from our IPD will also allow development and validation of multivariable prediction model for the relatively rare outcome of early onset pre-eclampsia. Trial registration: The project was registered on Prospero on the 27 November 2015 with ID: CRD42015029349.en_US
dc.description.sponsorshipFunding was recieved from the National Institute for Health Research - Health Technology Assessment programme.en_US
dc.format.extent16 - ?en_US
dc.languageengen_US
dc.language.isoenen_US
dc.relation.ispartofDiagn Progn Resen_US
dc.rightsThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
dc.subjectFetalen_US
dc.subjectIPDen_US
dc.subjectIndividual participant dataen_US
dc.subjectMaternalen_US
dc.subjectPre-eclampsiaen_US
dc.subjectPrediction modelen_US
dc.subjectPrognosisen_US
dc.titleExternal validation, update and development of prediction models for pre-eclampsia using an Individual Participant Data (IPD) meta-analysis: the International Prediction of Pregnancy Complication Network (IPPIC pre-eclampsia) protocol.en_US
dc.typeArticle
dc.rights.holder© The Author(s) 2017
dc.identifier.doi10.1186/s41512-017-0016-zen_US
pubs.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/31093545en_US
pubs.notesNot knownen_US
pubs.publication-statusPublished onlineen_US
pubs.volume1en_US
dcterms.dateAccepted2017-09-19en_US
qmul.funderAccuracy of clinical characteristics, biochemical and ultrasound markers in the prediction of pre-eclampsia: an Individual Participant Data (IPD) Meta-analysis::NIHR Evaluation, Trials and Studies Coordinating Centreen_US


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