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Record W4407592940 · doi:10.1097/aln.0000000000005418

Global Trends in Analgesic Opioid Use in Pregnancy: A Retrospective Cohort Study

2025· article· en· W4407592940 on OpenAlexafffundabout
Jonathan Brett, Carolyn E. Cesta, M. Gillies, Brian T. Bateman, Adrienne Y L Chan, Yongtai Cho, Jacqueline M. Cohen, Sarah Donald, Kari Furu, Mika Gissler, Tara Gomes, Alys Havard, Sonia Hernández–Dı́az, Miyuki Hsing‐Chun Hsieh, Krista F. Huybrechts, Erin Kelty, Edward Chia‐Cheng Lai, Shaleesa Ledlie, Maarit K. Leinonen, Lianne Parkin, Johan Reutfors, Ju‐Young Shin, C. Su, Bianca Varney, Ian Chi Kei Wong, Kenneth K. C. Man, Helga Zoëga

Bibliographic record

VenueAnesthesiology · 2025
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsInstitute for Clinical Evaluative SciencesUniversity of TorontoSt. Michael's Hospital
FundersHealth and Medical Research FundNational Science and Technology CouncilMedical Research CouncilNSW Ministry of HealthNational Health and Medical Research CouncilOntario Ministry of Health and Long-Term CareNorges ForskningsrådNational Health Research InstitutesWorld Health OrganizationEuropean CommissionDepartment of Health and Aged Care, Australian GovernmentUniversity of New South WalesHealth and Welfare Data Science CenterNational Institute for Health and Care ResearchAustralian GovernmentInstitute for Clinical Evaluative Sciences
KeywordsMedicineRetrospective cohort studyPregnancyAnalgesicOpioidObstetricsCohort studyOpioid-Related DisordersAnesthesiaInternal medicineOpioid epidemic

Abstract

fetched live from OpenAlex

BACKGROUND: Pain is common during pregnancy, yet there are few contemporary studies of opioid use in pregnancy. This study aimed to describe prescription analgesic opioid use during pregnancy across four regions: Oceania (New South Wales, Australia, and New Zealand), North America (Ontario, Canada, and United States), Northern Europe (Denmark, Finland, Iceland, Norway, Sweden, and United Kingdom), and East Asia (Hong Kong, South Korea, and Taiwan). METHODS: A common protocol was applied to population-based data to measure analgesic opioid dispensing or prescriptions during pregnancy before birth in 2000 to 2020. The populations captured included those with public and private insurance in the United States, a sample of primary care practices in the United Kingdom, and whole-of-population cohorts in the remainder of the locations. This study examined prevalence of use, defined as at least one dispensing or prescribing and estimated trends over time. Use by sociodemographic and pregnancy characteristics is described. RESULTS: Among a total of 20,306,228 pregnancies, 1,115,853 (55 per 1,000) had at least one analgesic opioid dispensing or prescription, ranging from 4 per 1,000 in the United Kingdom to 191 per 1,000 in the U.S. publicly insured population. The greatest relative decrease in prevalence was observed in Hong Kong (prevalence ratio, 0.2; 95% CI, 0.1 to 0.2 between 2005 and 2020), and the greatest increase was in Iceland (prevalence ratio, 4.4; 95% CI, 3.7 to 5.2 between 2004 and 2017). Codeine and tramadol were among the three most prevalent opioids in most populations. In a sensitivity analysis defining opioid use as two or more opioid -dispensing or -prescribing events, the prevalence of opioid use across populations was 17 per 1,000. CONCLUSIONS: In this large multinational study, wide global variation in the prevalence of analgesic opioid use in pregnancy was observed, yet patterns of use by sociodemographic and pregnancy characteristics were relatively consistent. Analgesic opioid use remained stable or downward trending over time in most, but not all, countries.

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)0.000
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 score0.007
Threshold uncertainty score0.699

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
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 head0.012
GPT teacher head0.287
Teacher spread0.275 · 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

Citations6
Published2025
Admission routes3
Has abstractyes

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