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Record W4382883435 · doi:10.1016/j.xagr.2023.100222

Hepcidin across pregnancy and its correlation with maternal markers of iron and inflammation, maternal body weight outcomes, and offspring neurodevelopmental outcomes: a systematic review and meta-analysis

2023· review· en· W4382883435 on OpenAlexafffund
Derrick Ssewanyana, Stephane Borque, Stephen J. Lye, Stephen G. Matthews

Bibliographic record

VenueAJOG Global Reports · 2023
Typereview
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsUniversity of AlbertaLunenfeld-Tanenbaum Research InstituteUniversity of Toronto
FundersTemerty Faculty of Medicine, University of TorontoCanadian Institutes of Health ResearchUniversity of Toronto
KeywordsHepcidinMedicineConfidence intervalOffspringPregnancyObstetricsFerritinBody mass indexMeta-analysisInternal medicinePhysiologyAnemiaBiology

Abstract

fetched live from OpenAlex

This study evaluated the correlation between maternal hepcidin and other biomarkers of iron status, markers of inflammation, and maternal body weight during pregnancy, as well as neurodevelopment in the offspring. PubMed, Web of Science, Scopus, and Embase were searched from inception until March 2022. Studies conducted among pregnant women without apparent pregnancy complications were included. Eligible studies reported correlation coefficients between maternal hepcidin and any outcomes of maternal biomarkers of iron status or inflammatory load during pregnancy, prenatal maternal body weight, and offspring neurodevelopment. Studies without correlation data were eligible if they quantitatively reported volumes of both maternal hepcidin and any marker of iron status and/or inflammatory load during gestation. Pooled correlation coefficients between maternal hepcidin and outcomes of interest were calculated using the Fisher r-to-Z transformation. Both fixed-effects and DerSimonian and Laird random-effects models were used to calculate pooled correlation coefficient. When meta-analysis was not feasible, results were descriptively synthesized. Forty-six studies with 6624 participants were eligible. Hepcidin was significantly correlated with hemoglobin in the third trimester (r=0.21; 95% confidence interval, 0.1–0.32); ferritin in the first (r=0.31; 95% confidence interval, 0.01–0.61) and third trimester (r=0.35; 95% confidence interval, 0.23–0.48); soluble transferrin receptor in the second trimester (r=−0.27; 95% confidence interval, −0.4 to −0.14); total iron-binding capacity in the second trimester (r=0.37; 95% confidence interval, 0.24–0.50); and serum iron in the third trimester (r=0.11; 95% confidence interval, 0.02–0.19). Hepcidin was significantly correlated with the inflammatory marker interleukin-6 in the third trimester (r=0.26; 95% confidence interval, 0.17–0.34) and C-reactive protein in the second (r=0.16; 95% confidence interval, 0.03–0.30) and third trimester (r=0.28; 95% confidence interval, 0.04–0.52). Four out of 5 studies reported weak-to-moderate positive correlation between hepcidin and body mass index. Hepcidin levels varied across body mass index categories. No single study reported the relationship between maternal hepcidin and neurodevelopment in offspring. Hepcidin weakly to moderately correlates with biomarkers of iron and inflammation in pregnancy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.755
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.030
GPT teacher head0.327
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2023
Admission routes2
Has abstractyes

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