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Record W4387841273 · doi:10.1093/humrep/dead211

A prospective cohort study of preconception COVID-19 vaccination and miscarriage

2023· article· en· W4387841273 on OpenAlexaboutno aff
Jennifer J. Yland, Amelia K. Wesselink, Annette K. Regan, Elizabeth E. Hatch, Kenneth J. Rothman, David A. Savitz, Tanran R. Wang, Krista F. Huybrechts, Sonia Hernández–Dı́az, Michael L. Eisenberg, Lauren A. Wise

Bibliographic record

VenueHuman Reproduction · 2023
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Impact on Reproduction
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentNational Institute of Allergy and Infectious DiseasesNational Science Foundation
KeywordsMiscarriageMedicinePregnancyVaccinationProspective cohort studyObstetricsCohort studyCohortGynecologyDemographyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

STUDY QUESTION: To what extent is preconception maternal or paternal coronavirus disease 2019 (COVID-19) vaccination associated with miscarriage incidence? SUMMARY ANSWER: COVID-19 vaccination in either partner at any time before conception is not associated with an increased rate of miscarriage. WHAT IS KNOWN ALREADY: Several observational studies have evaluated the safety of COVID-19 vaccination during pregnancy and found no association with miscarriage, though no study prospectively evaluated the risk of early miscarriage (gestational weeks [GW] <8) in relation to COVID-19 vaccination. Moreover, no study has evaluated the role of preconception vaccination in both male and female partners. STUDY DESIGN, SIZE, DURATION: An Internet-based, prospective preconception cohort study of couples residing in the USA and Canada. We analyzed data from 1815 female participants who conceived during December 2020-November 2022, including 1570 couples with data on male partner vaccination. PARTICIPANTS/MATERIALS, SETTING, METHODS: Eligible female participants were aged 21-45 years and were trying to conceive without use of fertility treatment at enrollment. Female participants completed questionnaires at baseline, every 8 weeks until pregnancy, and during early and late pregnancy; they could also invite their male partners to complete a baseline questionnaire. We collected data on COVID-19 vaccination (brand and date of doses), history of SARS-CoV-2 infection (yes/no and date of positive test), potential confounders (demographic, reproductive, and lifestyle characteristics), and pregnancy status on all questionnaires. Vaccination status was categorized as never (0 doses before conception), ever (≥1 dose before conception), having a full primary sequence before conception, and completing the full primary sequence ≤3 months before conception. These categories were not mutually exclusive. Participants were followed up from their first positive pregnancy test until miscarriage or a censoring event (induced abortion, ectopic pregnancy, loss to follow-up, 20 weeks' gestation), whichever occurred first. We estimated incidence rate ratios (IRRs) for miscarriage and corresponding 95% CIs using Cox proportional hazards models with GW as the time scale. We used propensity score fine stratification weights to adjust for confounding. MAIN RESULTS AND THE ROLE OF CHANCE: Among 1815 eligible female participants, 75% had received at least one dose of a COVID-19 vaccine by the time of conception. Almost one-quarter of pregnancies resulted in miscarriage, and 75% of miscarriages occurred <8 weeks' gestation. The propensity score-weighted IRR comparing female participants who received at least one dose any time before conception versus those who had not been vaccinated was 0.85 (95% CI: 0.63, 1.14). COVID-19 vaccination was not associated with increased risk of either early miscarriage (GW: <8) or late miscarriage (GW: 8-19). There was no indication of an increased risk of miscarriage associated with male partner vaccination (IRR = 0.90; 95% CI: 0.56, 1.44). LIMITATIONS, REASONS FOR CAUTION: The present study relied on self-reported vaccination status and infection history. Thus, there may be some non-differential misclassification of exposure status. While misclassification of miscarriage is also possible, the preconception cohort design and high prevalence of home pregnancy testing in this cohort reduced the potential for under-ascertainment of miscarriage. As in all observational studies, residual or unmeasured confounding is possible. WIDER IMPLICATIONS OF THE FINDINGS: This is the first study to evaluate prospectively the relation between preconception COVID-19 vaccination in both partners and miscarriage, with more complete ascertainment of early miscarriages than earlier studies of vaccination. The findings are informative for individuals planning a pregnancy and their healthcare providers. STUDY FUNDING/COMPETING INTEREST(S): This work was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the National Institute of Health [R01-HD086742 (PI: L.A.W.); R01-HD105863S1 (PI: L.A.W. and M.L.E.)], the National Institute of Allergy and Infectious Diseases (R03-AI154544; PI: A.K.R.), and the National Science Foundation (NSF-1914792; PI: L.A.W.). The funders had no role in the study design, data collection, analysis and interpretation of data, writing of the report, or the decision to submit the paper for publication. L.A.W. is a fibroid consultant for AbbVie, Inc. She also receives in-kind donations from Swiss Precision Diagnostics (Clearblue home pregnancy tests) and Kindara.com (fertility apps). M.L.E. received consulting fees from Ro, Hannah, Dadi, VSeat, and Underdog, holds stock in Ro, Hannah, Dadi, and Underdog, is a past president of SSMR, and is a board member of SMRU. K.F.H. reports being an investigator on grants to her institution from UCB and Takeda, unrelated to this study. S.H.-D. reports being an investigator on grants to her institution from Takeda, unrelated to this study, and a methods consultant for UCB and Roche for unrelated drugs. The authors report no other relationships or activities that could appear to have influenced the submitted work. TRIAL REGISTRATION NUMBER: N/A.

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)0.002
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 score0.041
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.059
GPT teacher head0.393
Teacher spread0.334 · 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".

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Citations11
Published2023
Admission routes1
Has abstractyes

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