Evidence map›Paper›PMID 35067676›Full record

ArticleJournal of perinatology : official journal of the California Perinatal Association2022

Targeted newborn metabolomics: prediction of gestational age from cord blood.

Elizabeth A Jasper, Scott P Oltman, Elizabeth E Rogers, John M Dagle, Jeffrey C Murray, Moses Kamya, Abel Kakuru, Richard Kajubi, Teddy Ochieng, Harriet Adrama and 8 more

Open access · greenAbstract read
In one paragraph

Article in Journal of perinatology : official journal of the California Perinatal Association, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 30% 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

5 citing papers in PubMed, 6 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

18 authors at 4 institutions in 2 countries.

Elizabeth A JasperDepartment of Epidemiology, University of Iowa, Iowa, IA, USA.
Scott P OltmanDepartment of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
Elizabeth E RogersDepartment of Pediatrics, University of California San Francisco, San Francisco, CA, USA.
John M DagleDepartment of Pediatrics, University of Iowa, Iowa, IA, USA.
Jeffrey C MurrayDepartment of Pediatrics, University of Iowa, Iowa, IA, USA.ORCID 0000-0001-6346-6551
Moses KamyaInfectious Diseases Research Collaboration, Kampala, Uganda.
Abel KakuruInfectious Diseases Research Collaboration, Kampala, Uganda.
Richard KajubiInfectious Diseases Research Collaboration, Kampala, Uganda.
Teddy OchiengInfectious Diseases Research Collaboration, Kampala, Uganda.
Harriet AdramaInfectious Diseases Research Collaboration, Kampala, Uganda.
Martin OkitwiInfectious Diseases Research Collaboration, Kampala, Uganda.
Peter OlwochInfectious Diseases Research Collaboration, Kampala, Uganda.
Prasanna JagannathanDepartment of Medicine, Stanford University Medical Center, Stanford, CA, USA.
Tamara D ClarkDepartment of Medicine, University of California, San Francisco School of Medicine, San Francisco, CA, USA.
Grant DorseyDepartment of Medicine, University of California, San Francisco School of Medicine, San Francisco, CA, USA.
Theodore RuelDepartment of Pediatrics, University of California, San Francisco School of Medicine, San Francisco, CA, USA.
Laura L Jelliffe-PawlowskiDepartment of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
Kelli K RyckmanDepartment of Epidemiology, University of Iowa, Iowa, IA, USA. Kelli-ryckman@uiowa.edu.ORCID 0000-0002-9496-4147
Infectious Diseases Research Collaboration · UGUniversity of California, San Francisco · USUniversity of Iowa · USStanford Medicine · US

Funding

The immunologic consequences of prenatal exposure to malariaP01HD059454 · NICHD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DORSEY, MATTHEW G · 2008 to 2017
$22.6M
Building Interdisciplinary Research Careers in Women's HealthK12HD043483 · NICHD · VANDERBILT UNIVERSITY MEDICAL CENTER · PI HARTMANN, KATHERINE E, MAJOR, AMY S · 2002 to 2023
$10.3M
NICHD NIH HHS K12 HD043483NICHD NIH HHS P01 HD059454
6 · The paper itself

Abstract

objectiveOur study sought to determine whether metabolites from a retrospective collection of banked cord blood specimens could accurately estimate gestational age and to validate these findings in cord blood samples from Busia, Uganda. STUDY

designForty-seven metabolites were measured by tandem mass spectrometry or enzymatic assays from 942 banked cord blood samples. Multiple linear regression was performed, and the best model was used to predict gestational age, in weeks, for 150 newborns from Busia, Uganda.

resultsThe model including metabolites and birthweight, predicted the gestational ages within 2 weeks for 76.7% of the Ugandan cohort. Importantly, this model estimated the prevalence of preterm birth <34 weeks closer to the actual prevalence (4.67% and 4.00%, respectively) than a model with only birthweight which overestimates the prevalence by 283%.

conclusionModels that include cord blood metabolites and birth weight appear to offer improvement in gestational age estimation over birth weight alone.

Indexed as

Fetal BloodPremature BirthBirth WeightFemaleGestational AgeHumansInfant, NewbornMetabolomicsPregnancyRetrospective Studies

Identifiers

PMID35067676
PMCPMC8830770
OpenAlexW4207052592

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.