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Enregistrement W3213206229 · doi:10.1177/03635465211059195

Anterior Shoulder Instability in Throwers and Overhead Athletes: Long-term Outcomes in a Geographic Cohort

2021· article· en· W3213206229 sur OpenAlexaboutno aff
Ryan R. Wilbur, Matthew B. Shirley, Richard F. Nauert, Matthew D. LaPrade, Kelechi R. Okoroha, Aaron J. Krych, Christopher L. Camp

Notice bibliographique

RevueThe American Journal of Sports Medicine · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueShoulder Injury and Treatment
Établissements canadiensnon disponible
Organismes subventionnairesNational Institute of Arthritis and Musculoskeletal and Skin DiseasesStrykerAmerican Orthopaedic Society for Sports MedicineMusculoskeletal Transplant FoundationHistogenicsArthrex
Mots-clésMedicineAthletesCohortThrowingPhysical therapyCohort studyPopulationInternal medicineEnvironmental health

Résumé

récupéré en direct d'OpenAlex

Background: Athletes of all sports often have shoulder instability, most commonly as anterior shoulder instability (ASI). For overhead athletes (OHAs) and those participating in throwing sports, clinical and surgical decision making can be difficult owing to a lack of long-term outcome studies in this population of athletes. Purpose/Hypothesis: To report presentation characteristics, pathology, treatment strategies, and outcomes of ASI in OHAs and throwers in a geographic cohort. We hypothesized that OHAs and throwers would have similar presenting characteristics, management strategies, and clinical outcomes but lower rates of return to play (RTP) when compared with non-OHAs (NOHAs) and nonthrowers, respectively. Study Design: Cohort study; Level of evidence, 3. Methods: An established geographic medical record system was used to identify OHAs diagnosed with ASI in the dominant shoulder. An overall 57 OHAs with ASI were matched 1:2 with 114 NOHAs with ASI. Of the OHAs, 40 were throwers. Sports considered overhead were volleyball, swimming, racquet sports, baseball, and softball, while baseball and softball composed the thrower subgroup. Records were reviewed for patient characteristics, type of sport, imaging findings, treatment strategies, and surgical details. Patients were contacted to collect Western Ontario Shoulder Instability index (WOSI) scores and RTP data. Statistical analysis compared throwers with nonthrowers and OHAs with NOHAs. Results: Four patients, 3 NOHAs and 1 thrower, were lost to follow-up at 6 months. Clinical follow-up for the remaining 167 patients (98%) was 11.9 ± 7.2 years (mean ± SD). Of the 171 patients included, an overall 41 (36%) NOHAs, 29 (51%) OHAs, and 22 (55%) throwers were able to be contacted for WOSI scores and RTP data. OHAs were more likely to initially present with subluxations (56%; P = .030). NOHAs were more likely to have dislocations (80%; P = .018). The number of instability events at presentation was similar. OHAs were more likely to undergo initial operative management. Differences in rates of recurrent instability were not significant after initial nonoperative management (NOHAs, 37.1% vs OHAs, 28.6% [ P = .331] and throwers, 21.2% [ P = .094]) and surgery (NOHAs, 20.5% vs OHAs, 13.0% [ P = .516] and throwers, 9.1% [ P = .662]). Rates of revision surgery were similar (NOHAs, 18.0% vs OHAs, 8.7% [ P = .464] and throwers, 18.2% [ P > .999]). RTP rates were 80.5% in NOHAs, as compared with 71.4% in OHAs ( P = .381) and 63.6% in throwers ( P = .143). Median WOSI scores were 40 for NOHAs, as compared with 28 in OHAs ( P = .425) and 28 in throwers ( P = .615). Conclusion: In a 1:2 matched comparison of general population athletes, throwers and OHAs were more likely to have more subtle instability, as evidenced by higher rates of subluxations rather than frank dislocations, when compared with NOHAs. Despite differences in presentation and the unique sport demands of OHAs, rates of recurrent instability and revision surgery were similar across groups. Similar outcomes in terms of RTP, level of RTP, and WOSI scores were achieved for OHAs and NOHAs, but these results must be interpreted with caution given the limited sample size.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,011
Score d'incertitude au seuil0,022

Scores du classifieur distillé par catégorie (deux têtes)

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

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 Opus0,020
Tête enseignante GPT0,328
Écart entre enseignants0,308 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
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

Citations20
Publié2021
Routes d'admission1
Résumé présentoui

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Même revueThe American Journal of Sports MedicineMême sujetShoulder Injury and TreatmentTravaux en français237 207