Evidence map›Paper›PMID 28570613›Full record

ArticlePloS one2017

Clinical, ultrasound and molecular biomarkers for early prediction of large for gestational age infants in nulliparous women: An international prospective cohort study.

Matias C Vieira, Lesley M E McCowan, Alexandra Gillett, Lucilla Poston, Elaine Fyfe, Gustaaf A Dekker, Philip N Baker, James J Walker, Louise C Kenny, Dharmintra Pasupathy and 1 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 15 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 6 institutions in 5 countries.

Matias C VieiraDivision of Women's Health, Women's Health Academic Centre, King's College London and King's Health Partners, London, United Kingdom.ORCID http://orcid.org/0000-0002-8076-4275
Lesley M E McCowanDepartment of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.
Alexandra GillettDivision of Women's Health, Women's Health Academic Centre, King's College London and King's Health Partners, London, United Kingdom.
Lucilla PostonDivision of Women's Health, Women's Health Academic Centre, King's College London and King's Health Partners, London, United Kingdom.
Elaine FyfeDepartment of Obstetrics and Gynaecology, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.
Gustaaf A DekkerWomen's and Children's Division Lyell McEwin Hospital, University of Adelaide, Adelaide, South Australia, Australia.
Philip N BakerCollege of Medicine, Biological Sciences & Psychology, University of Leicester, Leicester, United Kingdom.
James J WalkerDepartment of Obstetrics and Gynaecology, Leeds Institute of Biomedical & Clinical Sciences, University of Leeds, Leeds, United Kingdom.
Louise C KennyThe Irish Centre for Fetal and Neonatal Translational Research (INFANT), Department of Obstetrics and Gynaecology, University College Cork, Cork University Maternity Hospital, Wilton, Cork, Ireland.
Dharmintra PasupathyDivision of Women's Health, Women's Health Academic Centre, King's College London and King's Health Partners, London, United Kingdom.
SCOPE Consortium
King's College London · GBUniversity of Auckland · NZLyell McEwin Hospital · AUUniversity College Cork · IEUniversity of Leeds · GBUniversity of Leicester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo develop a prediction model for term infants born large for gestational age (LGA) by customised birthweight centiles.

methodsInternational prospective cohort of nulliparous women with singleton pregnancy recruited to the Screening for Pregnancy Endpoints (SCOPE) study. LGA was defined as birthweight above the 90th customised centile, including adjustment for parity, ethnicity, maternal height and weight, fetal gender and gestational age. Clinical risk factors, ultrasound parameters and biomarkers at 14-16 or 19-21 weeks were combined into a prediction model for LGA infants at term using stepwise logistic regression in a training dataset. Prediction performance was assessed in a validation dataset using area under the Receiver Operating Characteristics curve (AUC) and detection rate at fixed false positive rates.

resultsThe prevalence of LGA at term was 8.8% (n = 491/5628). Clinical and ultrasound factors selected in the prediction model for LGA infants were maternal birthweight, gestational weight gain between 14-16 and 19-21 weeks, and fetal abdominal circumference, head circumference and uterine artery Doppler resistance index at 19-21 weeks (AUC 0.67; 95%CI 0.63-0.71). Sensitivity of this model was 24% and 49% for a fixed false positive rate of 10% and 25%, respectively. The addition of biomarkers resulted in selection of random glucose, LDL-cholesterol, vascular endothelial growth factor receptor-1 (VEGFR1) and neutrophil gelatinase-associated lipocalin (NGAL), but with minimal improvement in model performance (AUC 0.69; 95%CI 0.65-0.73). Sensitivity of the full model was 26% and 50% for a fixed false positive rate of 10% and 25%, respectively.

conclusionPrediction of LGA infants at term has limited diagnostic performance before 22 weeks but may have a role in contingency screening in later pregnancy.

Indexed as

BiomarkersBirth WeightGestational AgeUltrasonography, PrenatalAdultFemaleHumansInternationalityPregnancyProspective StudiesYoung AdultBiomarkers

Identifiers

PMID28570613
PMCPMC5453528
OpenAlexW2620967115

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.