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Record W4415533725 · doi:10.1016/j.jogc.2025.103159

SARS-CoV-2 Vaccination and Disorders of Menstruation: A Population-Based Cohort Study

2025· article· en· W4415533725 on OpenAlexafffundvenueabout
Maria P. Vélez, Jonas Shellenberger, Joel G. Ray

Bibliographic record

VenueJournal of Obstetrics and Gynaecology Canada · 2025
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Impact on Reproduction
Canadian institutionsQueen's UniversityMcGill UniversitySt. Michael's HospitalMcGill University Health Centre
FundersCanadian Institutes of Health ResearchOntario Ministry of Health and Long-Term CareInstitute for Clinical Evaluative Sciences
KeywordsVaccinationCohort studyReceiptDiagnosis codeCohortMenstruation

Abstract

fetched live from OpenAlex

This population-based study evaluated the association between SARS-CoV-2 vaccination and disorders of menstruation among all women in Ontario aged 18-44 years. Study exposure was receipt of a first dose of any SARS-CoV-2 vaccine from December 2021 to December 2022, handled in a time-varying manner. The outcome was an incident diagnosis of a disorder of menstruation, defined as 2 medical encounters billed as International Classification of Diseases, Ninth Revision diagnosis code 626 up to December 2023. Included were 2 114 589 women, of whom 44.7% were vaccinated against SARS-CoV-2. Disorders of menstruation occurred at a rate of 15.9 per 1000 person-years among vaccinated women, in contrast to a rate of 26.4 per 1000 person-years among unvaccinated women (adjusted rate ratio 0.60; 95% CI 0.59-0.60), supporting a lack of association between SARS-CoV-2 vaccination and an increased risk of disorders of menstruation.

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)0.000
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
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 head0.296
Teacher spread0.283 · 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 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

Citations0
Published2025
Admission routes4
Has abstractyes

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