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Unintentional Pediatric Cannabis Exposures After Legalization of Recreational Cannabis in Canada

2022· article· en· W4205668343 on OpenAlexafffundabout
Daniel T. Myran, Nathan Cantor, Yaron Finkelstein, Michael Pugliese, Astrid Guttmann, Rebecca Jesseman, Peter Tanuseputro

Bibliographic record

VenueJAMA Network Open · 2022
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of OttawaInstitute for Clinical Evaluative SciencesCanadian Centre on Substance Use and AddictionUniversity of TorontoOttawa Hospital
FundersInstitute for Clinical Evaluative SciencesCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsCannabisLegalizationRecreational useRecreationMarijuana smokingEnvironmental healthRecreational DrugMedicinePsychiatryPolitical scienceSubstance abuseDrugLaw

Abstract

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approach to legalizing recreational cannabis.Initially, the sale of cannabis flower, seeds, and oils was permitted, and after 1 year, this expanded to a wider variety of products, including cannabis edibles.4 We evaluated changes in pediatric emergency department (ED) visits and hospitalizations due to cannabis exposures associated with these changes. MethodsThis repeated cross-sectional study was authorized under section 45 of Ontario's Personal Health Information Protection Act and approved by the privacy and legal office of ICES (formerly the Institute for Clinical Evaluative Sciences).Section 45 allows ICES to collect personal health information without consent for the purpose of health system evaluation and improvement.We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cross-sectional studies.We identified all ED visits and related hospitalizations due to cannabis exposures among 2.35 million children aged 0 to 9 years in Ontario, Canada, between January 1, 2016, and March 31, 2021.We compared trends and characteristics of ED visits over 3 periods: prelegalization (January 2016-September 2018); the period after legalization of flower products, or period 1 (October 2018-January 2020); and the period after commercial edibles became available, or period 2 (February 2020-March 2021).Poisson models were used to calculate incidence rate ratios (IRRs) for change in monthly rates of visits.Health administrative data sets were linked using encoded identifiers and analyzed at ICES (eMethods in the Supplement).All tests of significance were 2-sided, and P values < .05were considered statistically significant.Data analysis was conducted from June through August 2021 using Stata statistical software version 17.0 (StataCorp). ResultsThere were 522 ED visits due to cannabis exposures among children (mean [SD] age, 3.8 [2.6] years; 281 visits [53.8%] among boys) including 81 visits during prelegalization, 124 visits during period 1, and 317 visits during period 2. The proportion of cannabis-related ED visits with hospitalization increased significantly after the introduction of edibles (122 visits [38.5%] during period 2 vs 29 visits [23.4%] during period 1 and 20 visits [24.7%] during the prelegalization period; P = .002).There were 19 ED visits (3.6%) with intensive care unit admission; no deaths were recorded (Table ).Rates of ED visits associated with cannabis exposures increased from January 2016 to March 2021 (Figure).Period 1 (IRR, 3.13; 95% CI, 2.37-4.16;P < .001)and period 2 (IRR, 9.12; 95% CI, 7.15-11.65;P < .001)were associated with increases in visits compared with the prelegalization period, + Supplemental content

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)0.000
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 score0.026
Threshold uncertainty score0.189

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.268
Teacher spread0.254 · 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".

Quick stats

Citations60
Published2022
Admission routes3
Has abstractyes

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