Evidence map›Paper›PMID 40323295›Full record

ArticleJournal of proteome research2025

Maternal Plasma Proteins Associated with Birth Weight: A Longitudinal, Large Scale Proteomic Study.

Ina Jungersen Andresen, Ane Cecilie Westerberg, Marie Cecilie Paasche Roland, Manuela Zucknick, Trond Melbye Michelsen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of proteome research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
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

5 authors.

Ina Jungersen AndresenDepartment of Obstetrics, Division of Obstetrics and Gynecology, Oslo University Hospital, 0372 Oslo, Norway.ORCID 0009-0003-2837-6210
Ane Cecilie WesterbergDepartment of Obstetrics, Division of Obstetrics and Gynecology, Oslo University Hospital, 0372 Oslo, Norway.
Marie Cecilie Paasche RolandDepartment of Obstetrics, Division of Obstetrics and Gynecology, Oslo University Hospital, 0372 Oslo, Norway.
Manuela ZucknickDepartment of Biostatistics, Oslo Centre for Biostatistics and Epidemiology, University of Oslo, 0372 Oslo, Norway.
Trond Melbye MichelsenDepartment of Obstetrics, Division of Obstetrics and Gynecology, Oslo University Hospital, 0372 Oslo, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Small infants for gestational age (SGA) and large infants for gestational age (LGA) have increased risk of complications during delivery and later in life. Prediction of the fetal weight is currently limited to biometric parameters obtained by ultrasound scans that can be imprecise. Biomarkers of fetal growth would be crucial for tailoring clinical management and optimizing outcomes for the mother and child. Seventy pregnant women participated in the current study, including 58, 7, and 5 giving birth to adequate for gestational age (AGA), SGA, and LGA infants, respectively. Maternal venous blood was drawn at gestational weeks 12-19, 21-27, and 28-34 and quantified for nearly 5000 proteins on the SomaLogic platform. We used machine learning algorithms with leave-one-out cross-validation to construct multiprotein models for prediction of birth weight groups. Random forest models using only 20 predefined proteins (selected by moderated

Indexed as

Birth WeightBlood ProteinsFetal MacrosomiaProteomicsAdultBiomarkersFemaleGestational AgeHumansInfant, NewbornInfant, Small for Gestational AgeLongitudinal StudiesMachine LearningPregnancyProteomeBiomarkersBlood ProteinsProteomeBiomarkersFetal growthLarge for gestational ageLongitudinalPregnancyProteomicsSmall for gestational ageSomaLogic

Identifiers

PMID40323295
PMCPMC12235715

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.