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Association of Maternal Opioid Use in Pregnancy With Adverse Perinatal Outcomes in Ontario, Canada, From 2012 to 2018

2020· article· en· W3045695273 on OpenAlexafffundabout
Daniel J. Corsi, Helen Hsu, Deshayne B. Fell, Shi Wu Wen, Mark Walker

Bibliographic record

VenueJAMA Network Open · 2020
Typearticle
Languageen
FieldMedicine
TopicPrenatal Substance Exposure Effects
Canadian institutionsChildren's Hospital of Eastern OntarioOttawa HospitalUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsMedicineObstetricsPregnancyGestational agePopulationPoisson regressionApgar scorePrenatal careRetrospective cohort studyPediatricsInternal medicineEnvironmental health

Abstract

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Importance: A recent epidemic of opioid abuse has been described in many communities, although population-based data on trends in use in pregnancy and perinatal outcomes after in utero exposure remain limited. Objective: To assess trends in prenatal opioid use and the potential association between prenatal opioid use and preterm birth and adverse perinatal outcomes. Design, Setting, and Participants: This population-based retrospective cohort study covered live births and stillbirths among adolescents and women 15 years and older from April 1, 2012, to March 31, 2018, in Ontario, Canada. Data were analyzed from July 29 to October 15, 2019. Exposures: Any opioid use in pregnancy, ascertained through self-reporting and routine prenatal care. Main Outcome and Measures: The primary outcome was preterm birth before a gestational age of 37 weeks. Separate indicators for birth occurring at gestational ages of 34 to 36 weeks (plus 6 to 7 days; late preterm), 32 to 33 weeks (plus 6 to 7 days), 28 to 31 weeks (plus 6 to 7 days), and less than 28 weeks (very preterm birth). Secondary outcomes included small for gestational age, stillbirth, transfer to neonatal intensive care, and 5-minute Apgar score. Coarsened exact matching techniques and Poisson regression models were used to estimate the risk difference and relative risk (RR) of outcomes associated with cannabis exposure to control for confounding. Results: Among 710 911 women included in the analytic sample (mean [SD] age, 30.4 [5.3] years), 8059 used opioids (1.1%), with prevalence decreasing from 1.31% (95% CI, 1.25%-1.38%) in fiscal year 2012-2013 to 1.05% (95% CI, 0.99%-1.11%) in fiscal year 2017-2018 (P < .001 for trend). Use was highest among women in the lowest quintile of area-level income (2.36% vs 0.56% in the highest quintile; RR, 3.86; 95% CI, 3.58-4.15) and did not decrease over time in this group (from 2.63% [95% CI, 2.41%-2.87%] in 2012-2013 to 2.35% [95% CI, 2.14%-2.58%] in 2017-2018; P = .23 for trend). The crude rate of preterm birth at a gestational age of less than 37 weeks was 14.0% (n = 1127) among women with reported use in pregnancy and 6.0% (n = 42 226) among women who did not use opioids in the unmatched cohort. The adjusted RR for preterm birth before a gestational age of 37 weeks was 1.63 (95% CI, 1.52-1.75) among opioid users compared with nonusers and 1.77 (95% CI, 1.35-2.31) for preterm birth before 32 weeks. Among newborns, risk for neonatal intensive care was 40.5% with perinatal exposure to opioids compared with 13.9% in unexposed infants (RR, 2.91; 95% CI, 2.80-3.03). Conclusions and Relevance: Rates of opioid use in pregnancy have declined in recent years, although use remains significantly higher among lower-income women. In this large population-based cohort, opioid use in pregnancy was associated with an increased risk of preterm birth and admission to a neonatal intensive care unit.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.034
Threshold uncertainty score0.250

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.004
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.228
Teacher spread0.214 · 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 source (direct Gemma or distilled Codex), 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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Citations69
Published2020
Admission routes3
Has abstractyes

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