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Record W2080506894 · doi:10.1080/01443610802628528

The effectiveness of discontinuing iron-containing prenatal multivitamins on reducing the severity of nausea and vomiting of pregnancy

2009· article· en· W2080506894 on OpenAlexaffabout
Simerpal K. Gill, Caroline Maltepe, Gideon Koren

Bibliographic record

VenueJournal of Obstetrics and Gynaecology · 2009
Typearticle
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsUniversity of TorontoSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsMedicineNauseaMultivitaminPregnancyDiscontinuationVomitingProspective cohort studyObstetricsPediatricsInternal medicineVitamin

Abstract

fetched live from OpenAlex

Nausea and vomiting of pregnancy (NVP) is experienced by the majority of pregnant women, and can negatively affect a women's quality of life. It has been suggested in observational studies that iron-containing prenatal multivitamins may increase the severity of NVP. The objective of this study was to determine whether decreasing iron exposure can mitigate NVP symptoms. Data were collected from a prospective cohort at the Motherisk Program in Toronto. Women (n = 97) seeking advice on managing severe NVP were advised to discontinue prenatal multivitamin administration and switch to folic acid, an adult multivitamin or a children's chewable multivitamin. Two-thirds (63 out of 97) (p < 0.001) of those women qualitatively reported an improvement in NVP symptoms after discontinuation of iron-containing prenatal multivitamins. These findings were verified quantitatively using both the pregnancy-unique quantification of emesis and nausea (PUQE) (p < 0.001) and well-being (p < 0.001) scoring systems. This is the first interventional study showing that discontinuation of iron results in improvement of NVP symptoms. Our data suggest that avoiding iron-containing prenatal multivitamins in the first trimester is effective in improving NVP symptoms in the majority of pregnant women suffering from morning sickness.

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)0.002
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.768
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.013
GPT teacher head0.278
Teacher spread0.265 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations32
Published2009
Admission routes2
Has abstractyes

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