High‐‘n’‐dry? A comparison of cannabis and alcohol use in drivers presenting to hospital after a vehicular collision
Notice bibliographique
Résumé
DESIGN: This was a prospective observational study. BACKGROUND AND AIMS: The characteristics of cannabis-involved motor vehicle collisions are poorly understood. This study of injured drivers identifies demographic and collision characteristics associated with high tetrahydrocannabinol (THC) concentrations. SETTING: The study was conducted in 15 Canadian trauma centres between January 2018 and December 2021. CASES: The cases (n = 6956) comprised injured drivers who required blood testing as part of routine trauma care. MEASUREMENTS: We quantified whole blood THC and blood alcohol concentration (BAC) and recorded driver sex, age and postal code, time of crash, crash type and injury severity. We defined three driver groups: high THC (THC ≥ 5 ng/ml and BAC = 0), high alcohol (BAC ≥ 0.08% and THC = 0) and THC/BAC-negative (THC = 0 = BAC). We used logistic regression techniques to identify factors associated with group membership. FINDINGS: Most injured drivers (70.2%) were THC/BAC-negative; 1274 (18.3%) had THC > 0, including 186 (2.7%) in the high THC group; 1161 (16.7%) had BAC > 0, including 606 (8.7%) in the high BAC group. Males and drivers aged less than 45 years had higher adjusted odds of being in the high THC group (versus the THC/BAC-negative group). Importantly, 4.6% of drivers aged less than 19 years had THC ≥ 5 ng/ml, and drivers aged less than 19 years had higher unadjusted odds of being in the high THC group than drivers aged 45-54 years. Males, drivers aged 19-44 years, rural drivers, seriously injured drivers and drivers injured in single-vehicle, night-time or weekend collisions had higher adjusted odds ratios (aORs) for being in the high alcohol group (versus THC/BAC-negative). Drivers aged less than 35 or more than 65 years and drivers involved in multi-vehicle, daytime or weekday collisions had higher adjusted odds for being in the high THC group (versus the high BAC group). CONCLUSIONS: In Canada, risk factors for cannabis-related motor vehicle collisions appear to differ from those for alcohol-related motor vehicle collisions. The collision factors associated with alcohol (single-vehicle, night-time, weekend, rural, serious injury) are not associated with cannabis-related collisions. Demographic factors (young drivers, male drivers) are associated with both alcohol and cannabis-related collisions, but are more strongly associated with cannabis-related collisions.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».