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Record W6926718196 · doi:10.25384/sage.c.6433756.v1

Prevalence of Alcohol and Other Drug Use in Patients Presenting to Hospital for Violence-Related Injuries: A Systematic Review

2023· other· en· W6926718196 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSage Journals Data · 2023
Typeother
Languageen
FieldMedicine
TopicCystic Fibrosis Research Advances
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPoison controlInjury preventionOccupational safety and healthObservational studyDrugSuicide preventionSubstance useHuman factors and ergonomics

Abstract

fetched live from OpenAlex

Substance use is a risk factor for being both a perpetrator and a victim of violence. The aim of this systematic review was to report the prevalence of acute pre-injury substance use in patients with violence-related injuries. Systematic searches were used to identify observational studies that included patients aged ≥15 years presenting to hospital after violence-related injuries and used objective toxicology measures to report prevalence of acute pre-injury substance use. Studies were grouped based on injury cause (any violence-related, assault, firearm, and other penetrating injuries including stab and incised wounds) and substance type (any substance, alcohol only, drugs other than alcohol only), and they were summarized using narrative synthesis and meta-analyses. This review included 28 studies. Alcohol was detected in 13%–66% of any violence-related injuries (five studies), 4%–71% of assaults (13 studies), 21%–45% of firearm injuries (six studies; pooled estimate = 41%, 95% CI: 40%–42%, <i>n</i> = 9,190), and 9%–66% of other penetrating injuries (nine studies; pooled estimate = 60%, 95% CI: 56%–64%, <i>n</i> = 6,950). Drugs other than alcohol were detected in 37% of any violence-related injuries (one study), 39% of firearm injuries (one study), 7%–49% of assaults (five studies), and 5%–66% of penetrating injuries (three studies). The prevalence of any substance varied across injury categories: any violence-related injuries = 76%–77% (three studies), assaults = 40%–73% (six studies), firearms = n/a, other penetrating injuries = 26%–45% (four studies; pooled estimate = 30%, 95% CI: 24%–37%, <i>n</i> = 319).Overall, substance use was frequently detected in patients presenting to hospital for violence-related injuries. Quantification of substance use in violence-related injuries provides a benchmark for harm reduction and injury prevention strategies.

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.

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)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.156
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.043
GPT teacher head0.372
Teacher spread0.329 · 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