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Record W2912633929 · doi:10.1024/0300-9831/a000507

Disparities in the timing and measurement methods to assess vitamin D status during pregnancy: A Narrative Review

2018· review· en· W2912633929 on OpenAlexaff
Claudia Savard, Claudia Gagnon, Anne‐Sophie Morisset

Bibliographic record

VenueInternational Journal for Vitamin and Nutrition Research · 2018
Typereview
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPregnancyConfoundingMedicineVitamin D and neurologyGestationProspective cohort studyvitamin D deficiencyPhysiologyNarrative reviewObstetricsInternal medicineBiologyIntensive care medicine

Abstract

fetched live from OpenAlex

Studies that examined associations between low circulating 25-hydroxyvitamin D (25(OH)D) and adverse pregnancy outcomes used various designs, assay methods and time points for measurement of 25(OH)D concentrations, which creates some confusion in the current literature. We aimed to investigate the variability in the timing and measurement methods used to evaluate vitamin D status during pregnancy. Analysis of 198 studies published between 1976 and 2017 showed an important variability in the choice of 1) threshold values for 25(OH)D insufficiency or deficiency, 2) 25(OH)D measurement methods, and 3) trimester in which 25(OH)D concentrations were measured. Blood samples were taken once during pregnancy in a large majority of studies, which may not be representative of vitamin D status throughout pregnancy. Most studies reported adjustment for confounding factors including season of blood sampling, but very few studies used the 25(OH)D gold standard assay, the LC-MS/MS. Prospective studies assessing maternal 25(OH)D concentrations 1) by standardized and validated methods, 2) at various time points during pregnancy, and 3) after considering potential confounding factors, are needed.

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)0.008
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.814
Threshold uncertainty score0.917

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.392
GPT teacher head0.576
Teacher spread0.184 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
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

Citations8
Published2018
Admission routes1
Has abstractyes

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