Notice bibliographique
Résumé
Re: S Thakore, J Tram, BE Hagel, T Kyle, T Senger, F Belanger. Injuries among wheeled shoe users: A comparison with other nonmotorized wheeled activities. Paediatr Child Health 2009;14(8):509–513. To the Editor; I would like to share with your readers the results of a Canadian Hospitals Injury Reporting and Prevention Program database analysis that were reported at a Canadian Society of Epidemiology and Biostatistics conference in 2003. A total of 3051 records from April 1990 to June 2002 from the Nova Scotia Canadian Hospitals Injury Reporting and Prevention Program database involving nonmotorized wheeled sports were analyzed. χ2 tests were performed for three pairwise comparisons among injured cyclists, skate-boarders and in-line skaters. Scooters were not included because the demographic was younger and significantly fewer records were available, and ‘Heelys’ had not yet made their debut in Nova Scotia. Of note, helmet legislation for cycling was introduced in Nova Scotia in 1997, while helmet legislation for all wheeled sports was introduced in 2003 after this study was completed. The sample included 71% male subjects (average age 10.3 years [12.8 years for skateboarding and 11.6 years for in-line skating]); 78.9% of the sample were injured while cycling, 12.6% while skateboarding and the remaining 8.5% while in-line skating. The admission rate was equal across all age groups at 10% and included a predominance of admissions related to fractures. Fractures comprised 32% of the injuries overall. Fractures were more common in in-line skating (53%) and skate-boarding (35%) than in cycling (26%) (P<0.02); however, more cyclists were admitted with their fractures than in-line skaters (26% versus 16%; P=0.02), with skateboarders (24%) being similar to cyclists. This would suggest that the fractures sustained in in-line skating could be of a less severe nature. Two per cent of in-line skaters wore protective gear other than helmets, while 1% of skateboarders and fewer than 0.1% of cyclists reported the use of additional protective gear. Head injuries (n=200) consisted of 7% of total injuries. Of these head injuries, 184 (92%) were related to cycling. When potentially confounding factors were included in a logistic regression model, the risk of head injury from skate-boarding had an adjusted OR of 0.24 (95% CI 0.12 to 0.47) and the risk from in-line skating had an adjusted OR of 0.34 (95% CI 0.16 to 0.74) relative to cycling. Wearing a helmet gave an adjusted OR of 0.43 (95% CI 0.31 to 0.61) for head injury across all sports. Looking at prehelmet legislation (1990 to 1996) versus posthelmet legislation (1997 to 2002), there was no significant decrease in the proportion of cyclists presenting with head injury (8.2% pre versus 7.1% post; P=0.28). Nevertheless, helmet use increased from 20% overall to 54% overall, and specifically from 21% to 63% in cycling, 1% to 22% in in-line skating and 0% to 46% in skateboarding. Compared with prehelmet legislation, the posthelmet legislation group had an OR of 4.6 (95% CI 3.9 to 5.4) for wearing a helmet. The incidence of cycling injuries in absolute numbers per year remained stable (range of 169 to 235 injuries per year), while skateboarding injuries increased (mean 21 injuries per year in the first five years to 44 injuries per year in last five years), reflecting an increase in participation rates. In summary, legislation was effective in increasing helmet use and reducing the risk of a head injury, but not in reducing the absolute proportion of head injuries in cyclists. In-line skaters should wear protective gear, in particular wrist guards, to prevent fractures.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,041 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,024 | 0,016 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,097 | 0,045 |
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 source (Gemma direct ou Codex distillé), 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 ».