Epidemiology of Injuries in Professional and Amateur Football Men (Part II)
Notice bibliographique
Résumé
Background (1): Men's football is a physically demanding contact sport that involves intermittent bouts of sprinting, jogging, walking, jumping and changes of direction. The physical demands of the game vary by level of play (amateur club, sub-elite and open club or international), but injury rates at all levels of the men's football game remain the highest of all sports. Objective: The aim of this study is to conduct a systematic review of data from the epidemiological literature regarding the profile, severity and mechanisms of injuries and the frequency of recurrent injuries in professional and amateur football players. Methods (2): A systematic review, according to PRISMA guidelines, was performed up to June 2023 in the databases of PubMed, Web of Science, Google academic, Google scholar and the Diva portal. Twenty-seven studies that reported data on the type, severity, recurrence and mechanisms of injury in professional and amateur men's football were selected and analyzed. Two reviewers independently audited data and assessed the study quality using the additional and adapted version of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and the Newcastle Ottawa Scale (NOS) to assess risk of bias for the quality of external validity. Results (3): In professional male football players, the mean prevalence of muscle/tendon injuries was 39.78%, followed by joint and ligament injuries-21.13%, contusions-17.86%, and fractures-3.27%, and for amateur football players, the prevalence's were 44.56% (muscle/tendon injuries), 27.62% (joint and ligament injuries), 15.0% (contusions) and 3.05% (fracture), respectively. The frequency of traumatic injuries was higher in amateur football players (76.88%) compared to professional football players (64.16%), the situation being reversed in the case of overuse injuries: 27.62% in professional football players and 21.13% in amateur football players. Most contact injuries were found in professional footballers (50.70%), with non-contact injuries predominating in amateur footballers (54.04%). The analysis of the severity of injuries showed that moderate injuries dominated in the two categories of footballers; the severe injuries in amateur footballers exceeded the severe injuries recorded in professional footballers by 9.60%. Recurrence proportions showed an inverse relationship with the level of play, being higher in amateur footballers (16.66%) compared to professional footballers (15.25%). Conclusions (4): Football-related injuries have a significant impact on professional and amateur football players and their short- and long-term health status. Knowing the frequency of severe diagnoses, such as strains, tears and cramps of the thigh muscles, ankle ligament sprains and hip/groin muscle strain requires the establishment of adequate programs to prevent them, especially in amateur football players, who are more prone to serious injuries.
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 | 0,008 | 0,026 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,004 |
| Bibliométrie | 0,018 | 0,014 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 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 ».