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Record W7117292460 · doi:10.1002/pds.70303

Medications Used Among Nonhospitalized Pregnant Women With <scp>COVID</scp> ‐19: A Prospective Individual Patient Data Meta‐Analysis in Europe and North America

2025· article· en· W7117292460 on OpenAlexafffund
Odette de Bruin, Émeline Maisonneuve, Eimir Hurley, Hedvig M E Nordeng, Anick Bérard, Odile E Sheehy, P. Kaul, Mayura U Shinde, Austin Cosgrove, Jennifer G. Lyons, Elizabeth Messenger‐Jones, Maria E. Kempner, Sengwee Toh, Wei Hua, José J. Hernández‐Muñoz, Leyla Şahin, Carolyn E. Cesta, David Hägg, Rosa Gini, Olga Paoletti, Beatriz Poblador‐Plou, Sue Jordan, Daniel Thayer, Clara L. Rodríguez‐Bernal, Francisco Sánchez‐Sáez, Régis Lassalle, Marie‐Agnès Bernard, Ema Alsina, Fariba Ahmadizar, Guillaume Favre, Alice Panchaud, Kitty W M Bloemenkamp, Kelly Plueschke, Corinne S de Vries, Satu J. Siiskonen, Miriam C J M Sturkenboom

Bibliographic record

VenuePharmacoepidemiology and Drug Safety · 2025
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Impact on Reproduction
Canadian institutionsUniversity of AlbertaUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersCanadian Institutes of Health ResearchU.S. Food and Drug AdministrationEuropean Medicines AgencyUniversiteit UtrechtCanada Foundation for Innovation
KeywordsAntithromboticPharmacoepidemiologyMultinational corporationPatient dataPublic healthMEDLINE

Abstract

fetched live from OpenAlex

ABSTRACT Aim To estimate the prevalence of medication use in nonhospitalized pregnant women with COVID‐19. Methods A prospective two‐stage individual patient meta‐analysis across 10 data sources in Europe and North America studied medication use among nonhospitalized pregnant women with COVID‐19 between January 2020 and December 2022. Comparisons were made between medication use within 30 days pre‐ and post‐COVID‐19 diagnosis in this cohort and two comparator groups: pregnant women without COVID‐19 and nonpregnant women with COVID‐19. Prevalence estimates were pooled using a random‐effects model stratified by trimester. Results 50 335 nonhospitalized pregnant women with COVID‐19 were identified. The pooled prevalence of antibacterial use in the third trimester was higher post‐COVID‐19 diagnosis (6.8%, 95% confidence interval [CI] = 5.5–8.4, I 2 = 94%) compared with the same women pre‐COVID‐19 (3.9%, 95% CI = 3.1–4.9, I 2 = 89%). Overall, pregnant women with COVID‐19 had higher medication use compared to pregnant women without COVID‐19, although the CIs of the prevalence overlapped. Post‐COVID‐19, antithrombotic prevalence was 4.5% (95% CI = 1.1–16.5, I 2 = 100%) among pregnant women with COVID‐19 in the third trimester, compared to 2.1% (95% CI = 1.2–3.6, I 2 = 99%) among those without COVID‐19 in the third trimester. Compared to nonpregnant women with COVID‐19, pregnant women with COVID‐19 were less likely to be prescribed analgesics, antiprotozoals, corticosteroids, psychoanaleptics and psycholeptics, and more likely to be prescribed antithrombotics, cough and cold and nasal preparations, and drugs used in diabetes across all trimesters. High heterogeneity existed in nearly all analyses. Conclusion This international meta‐analysis reveals low medication use and country‐specific variations, enhancing insight into the management of COVID‐19 in nonhospitalized pregnant women. Higher antithrombotic use post‐COVID‐19 suggests prophylactic treatment in this population, but variation between countries emphasizes the challenges of combining multinational data.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.932

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
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 head0.048
GPT teacher head0.359
Teacher spread0.311 · 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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Citations0
Published2025
Admission routes2
Has abstractyes

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