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Record W4386020013 · doi:10.1080/15563650.2023.2238121

Severe outcomes following pediatric cannabis intoxication: a prospective cohort study of an international toxicology surveillance registry

2023· article· en· W4386020013 on OpenAlexaff
Neta Cohen, Mathew Mathew, Jeffrey Brent, Paul M. Wax, Adrienne L. Davis, Cherie Obilom, Michele M. Burns, Joshua Canning, Kevin Baumgartner, Andrew Koons, Timothy J. Wiegand, Bryan Judge, Christopher Hoyte, James Chenoweth, Blake Froberg, Henry C. Farrar, Jennifer Carey, Robert G. Hendrickson, Michael Hodgman, E. Martin Caravati, Michael Christian, Brian Wolk, Steven A. Seifert, Yedidia Bentur, Michael Levine, Lynn A. Farrugia, David Vearrier, Alicia B. Minns, Joseph M. Kennedy, Ron I. Kirschner, Kim Aldy, Suzanne Schuh, Sharan Campleman, Shao Li, Daniel T. Myran, Lisa Feng, Stephen B. Freedman, Yaron Finkelstein

Bibliographic record

VenueClinical Toxicology · 2023
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversity of CalgaryBruyèreHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicinePolysubstance dependenceOdds ratioCannabisConfidence intervalProspective cohort studyInterquartile rangeEmergency departmentCohortCohort studyHazard ratioEmergency medicinePediatricsInternal medicineSubstance abusePsychiatry

Abstract

fetched live from OpenAlex

INTRODUCTION: An increasing number of jurisdictions have legalized recreational cannabis for adult use. The subsequent availability and marketing of recreational cannabis has led to a parallel increase in rates and severity of pediatric cannabis intoxications. We explored predictors of severe outcomes in pediatric patients who presented to the emergency department with cannabis intoxication. METHODS: In this prospective cohort study, we collected data on all pediatric patients (<18 years) who presented with cannabis intoxication from August 2017 through June 2020 to participating sites in the Toxicology Investigators Consortium. In cases that involved polysubstance exposure, patients were included if cannabis was a significant contributing agent. The primary outcome was a composite severe outcome endpoint, defined as an intensive care unit admission or in-hospital death. Covariates included relevant sociodemographic and exposure characteristics. RESULTS: < 0.001). As all children 10 years and younger ingested edibles, a dedicated multivariable analysis could not be performed (unadjusted odds ratio 3.3; 95% confidence interval: 1.6-6.7). CONCLUSIONS: Severe outcomes occurred for different reasons and were largely associated with the patient's age. Young children, all of whom were exposed to edibles, were at higher risk of severe outcomes. Teenagers with severe outcomes were frequently involved in polysubstance exposure, while psychosocial factors may have played a role.

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)0.004
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 score0.012
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.045
GPT teacher head0.427
Teacher spread0.382 · 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

Citations10
Published2023
Admission routes1
Has abstractyes

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