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Enregistrement W4231607899 · doi:10.1249/jsr.0000000000000724

Latest Clinical Research Published by ACSM

2020· article· en· W4231607899 sur OpenAlexaboutno aff
Robert B. Kiningham

Notice bibliographique

RevueCurrent Sports Medicine Reports · 2020
Typearticle
Langueen
DomaineMedicine
ThématiqueTraumatic Brain Injury Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésConcussionMedicineAthletesPhysical therapyNeurocognitiveInjury preventionSports medicinePoison controlCohortPhysical medicine and rehabilitationEmergency medicineInternal medicineCognitionPsychiatry

Résumé

récupéré en direct d'OpenAlex

No Clinical Predictors of Postconcussion Musculoskeletal Injury in College Athletes Several studies have observed an increased risk of musculoskeletal injuries after athletes return from a concussion. The underlying cause of this injury risk is unknown. In the June 2020 issue of Medicine & Science in Sports & Exercise® (MSSE), Buckley and colleagues (1) studied a cohort of 66 collegiate athletes with a diagnosis of concussion who had gone through a progressive return-to-play protocol before returning to their sport. A matched control design was used to determine if the concussed athletes were more likely to incur an acute lower extremity musculoskeletal (LE MSK) injury in the year after recovery compared with nonconcussed controls. Regression models were then used to see if there were concussion-related characteristics or demographic factors that predisposed athletes to an LE MSK injury after return from a concussion. All subjects participated in competitive athletics 1 year prior and 1 year after their concussion. Athletes with concurrent injuries that restricted return-to-play were excluded. Baseline and postconcussion assessment included a symptom checklist, Standard Assessment of Concussion mental screening, Balance Error Scoring System for stable posture control, ImPACT for neurocognition, Clinical Reaction Time, and King-Devick for horizontal saccade performance. The outcome of interest was an acute LE MSK that required at least 1 d of limited physical activity along with treatment that occurred within 365 d of returning to sport after a concussion. Chronic overuse injuries, contusions and abrasions, and medical illnesses were not included. Within the group of 66 concussed athletes, 53% were women. The average age was 20.0 ± 1.1 years. Football was the most common sport at 19.7%, followed by men's soccer and women’s volleyball at 10.6% each. Thirty-six of the concussed athletes were matched with athletes on the same team with comparable anthropometric characteristics and who played the same (or similar) position over the same period. Suitable control matches could not be found for the other 30 of the concussed cohort. A Cox proportional hazard model found that athletes who returned from a concussion were 78% more likely to sustain an acute LE MSK in the year following their concussion than nonconcussion-matched controls (hazard ratio, 1.78; 1.12 to 2.84). Thirty-six (54.5%) of the athletes suffered a LE MSK within the year after return to play from the concussion. A number of variables that could contribute to injury risk were looked at, including the severity of the concussion as measured by acute changes from baseline on the concussion assessment tests, days missed due to the concussion, presence of posttraumatic amnesia, loss of consciousness, subject demographics, sport, prior concussion, and prior musculoskeletal injuries. However, linear regression models did not identify any combination of participant demographics, injury characteristics, or concussion clinical outcomes that could predict subsequent LE MSK. This study supports previous studies that found an increased risk of MSK injury after return from concussion. However, no factors were identified that could explain why these athletes incurred more LE MSK injuries. The mean time to injury was 160.1 ± 101.7 d, so it is unlikely that acute effects of the concussion increased the injury risk. One hypothesis is that concussed athletes are just more “injury prone,” but in this study, there was no significant difference between groups in injury rates in the year prior to the concussion. A possible explanation is detection bias. In this study, an athlete needed only to be limited in their activity by 1 d to be classified as having an acute injury. Athletes and athletic trainers may be more “cautious” with a relatively minor injury after a concussion, and thereby the athlete is more likely to be classified as having an injury compared with the year before their concussion, or compared with athletes without a recent concussion. Bottom Line. Collegiate athletes were 78% more likely to sustain an acute LE MSK injury in the year following a concussion compared with tightly matched age, sex, and sport nonconcussed controls. However, no concussion-related assessments, injury characteristics, or demographic factors were found related to the increased risk of injury. Return to Sport Tests' Prognostic Value for Reinjury Risk After Anterior Cruciate Ligament Reconstruction Anterior cruciate ligament (ACL) ruptures are devastating knee injuries to young athletes. While ligament reconstruction surgeries are becoming more successful in returning athletes to sport, the reinjury rate remains high, with almost six times the risk of rerupture within 24 months of surgery compared with young adults without a history of an ACL tear (2). Physical therapy has been advocated as a requirement after ACL reconstruction surgery prior to return to sport (RTS), but there is no consensus on the specific criteria for allowing RTS. The purpose of this systematic review, also published in the June issue of MSSE, was to provide an evidence-based summary of RTS assessments after an ACL tear in their ability to predict ACL reinjury (3). English and German published studies that investigated RTS tests, including functional tests and patient self-report function, on their association with ACL reinjury rates. The population studied was male and female adolescents and adults who were involved in sports and suffered a primary unilateral ACL rupture and, subsequently, underwent ACL reconstruction and rehabilitation. Studies that involved subjects not involved in sports, or had no intention of returning to sport, were excluded, as were studies that included nonisolated ACL injuries that required repair or subjects who did not undergo surgery. Each study underwent an assessment of risk of bias according to the Cochrane Back Review Group recommendations, as well as an assessment of study quality on the Newcastle-Ottawa scale. Each study was assigned a level of evidence and quality of evidence rating per the GRADE recommendations. Eight published prospective cohort studies met the criteria for inclusion. The mean age for the injured athletes was 16.2 to 29.2 years. Both hamstring tendon grafts and bone-patella-tendon-bone graft ACL reconstructions were included. The reinjury incidence ranged from 1.5% to 37.5%. The authors categorized the RTP assessments into three groups: functional assessments, self-reported function, and kinematic assessments (primarily kinetics during drop jump landing). The functional assessments most commonly used were quadriceps and hamstring strength and hop tests. A 90% limb symmetry index (comparing the performance of the injured leg to the uninjured leg) is the standard threshold for RTP. Other references used for comparison are the estimated preinjury capacity (EPIC) of the uninjured leg and an absolute performance threshold, such a peak torque-to-body mass ratio or hop distance. The authors concluded that both EPIC and absolute performance thresholds were better at predicting reinjury risk compared with concurrent time limb comparisons, presumably due to deconditioning of the uninjured leg after the index injury. Self-reported function questionnaires also were reported to indicate increased reinjury risk. For example, a score of less than 44 on the quality of life subsection of the Knee Injury and Osteoarthritis Score identified patients at high risk of reinjury. Even more dramatic was a study that found that patients with a Tampa Scale of Kinesiophobia (a measure of fear of reinjury) score greater than or equal to 19 had a 13 times increased risk of a second ACL injury within 24 months. One study assessed the impact of advance neuromuscular training on hip and knee kinematics during drop jump landing and found that improved kinematics was associated with less ACL reinjury risk. This systematic review provided a good overview of the current state of reinjury risk assessment after ACL reconstruction, but conclusions were limited by the heterogeneity of the assessments and relatively few studies that met their quality threshold for inclusion. The results indicate directions for further research, and the need for more standardization of postrehabilitation evaluations prior to RTP. Bottom Line: Functional testing, scales of self-reported function, and kinematic assessment of jump landing all show potential utility in assessing reinjury risk after ACL reconstruction. It is likely that a combination of these assessments is needed to optimize the assessment of readiness for RTP.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,010
score de la tête « metaresearch » (Gemma)0,016
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche, Méta-épidémiologie (sens strict), Intégrité de la recherche, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,334
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0100,016
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,002
Études des sciences et des technologies0,0000,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,003
Charge utile insuffisante (le modèle a refusé de juger)0,0060,000

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.

Tête enseignante Opus0,395
Tête enseignante GPT0,530
Écart entre enseignants0,135 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

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