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Enregistrement W4400269458 · doi:10.1016/j.jseint.2024.06.009

Inter-rater and intrarater reliability of superior labrum anterior to posterior lesion classification using magnetic resonance arthrography

2024· article· es· W4400269458 sur OpenAlexaff
Austin W. Bowering, Brittany N. Bolt, Conall G. Donaghy, Nicholas Smith

Notice bibliographique

RevueJSES International · 2024
Typearticle
Languees
DomaineMedicine
ThématiqueShoulder Injury and Treatment
Établissements canadiensMemorial University of Newfoundland
Organismes subventionnairesnon disponible
Mots-clésMagnetic resonance imagingLabrumIntra-rater reliabilityMedicineLesionReliability (semiconductor)AnatomyRadiologySurgeryPhysicsArthroscopyInternal medicine

Résumé

récupéré en direct d'OpenAlex

BackgroundThe glenoid labrum is a fibrocartilaginous ring that affixes the joint capsule and ligaments of the glenohumeral joint. Superior labrum anterior to posterior (SLAP) lesions are a subset of injuries that affect the superior glenoid labrum, most common in laborers and overhead-throwing athletes. In 1990, Snyder et al classified SLAP lesions into one of four types. Later, Maffet et al expanded this scale to include three additional subclassifications. At present, arthroscopy is considered the gold standard for SLAP tear diagnosis. Classification under arthroscopy has demonstrated low to moderate inter-rater reliability. Magnetic resonance arthrography (MRa) is an alternate, less invasive test for diagnosing SLAP lesions. The reliability of MRa for diagnosing slap tears is uncertain.MethodsMagnetic resonance arthrograms were identified using the Picture Archiving and Communication System (PACS). In total, 273 shoulder arthrograms were reviewed, and 20 were selected with the desired pathology. Three orthopedic surgeons and three musculoskeletal radiologists were asked to classify the SLAP lesions into one of seven categories (Snyder & Maffet classification systems). Data was collected on two separate occasions at an interval of at least two months. Inter-rater and intrarater reliability were calculated using Fleiss Kappa and Cohen's Kappa, respectively.ResultsBetween all raters, there was poor inter-rater reliability for each round of data collection (κ = .177, κ = .124 for rounds 1 and 2, respectively). Between orthopedic surgeons, there were poor levels of agreement (κ = −.056, κ = .114), whereas, between radiologists, there was fair to moderate agreement (κ = 0.479, κ = 0.340). Within orthopedic raters, κ values ranged from −0.059 to 0.125, indicating, at best, poor intrarater reliability. Within radiologists, κ values ranged from 0.545 to 0.553, indicating moderate agreement within raters. The analysis determined that none of the orthopedic values for inter or intrarater reliability could be deemed statistically different from zero.ConclusionOverall, classification using MRa resulted in significant disagreement between and within raters. Trained radiologists demonstrated higher overall levels of agreement than orthopedic surgeons. In summary, when using MRa to assess SLAP lesions, Snyder and Maffet classification demonstrates poor reliability by orthopedic surgeons and moderate reliability when used by musculoskeletal radiologists. The glenoid labrum is a fibrocartilaginous ring that affixes the joint capsule and ligaments of the glenohumeral joint. Superior labrum anterior to posterior (SLAP) lesions are a subset of injuries that affect the superior glenoid labrum, most common in laborers and overhead-throwing athletes. In 1990, Snyder et al classified SLAP lesions into one of four types. Later, Maffet et al expanded this scale to include three additional subclassifications. At present, arthroscopy is considered the gold standard for SLAP tear diagnosis. Classification under arthroscopy has demonstrated low to moderate inter-rater reliability. Magnetic resonance arthrography (MRa) is an alternate, less invasive test for diagnosing SLAP lesions. The reliability of MRa for diagnosing slap tears is uncertain. Magnetic resonance arthrograms were identified using the Picture Archiving and Communication System (PACS). In total, 273 shoulder arthrograms were reviewed, and 20 were selected with the desired pathology. Three orthopedic surgeons and three musculoskeletal radiologists were asked to classify the SLAP lesions into one of seven categories (Snyder & Maffet classification systems). Data was collected on two separate occasions at an interval of at least two months. Inter-rater and intrarater reliability were calculated using Fleiss Kappa and Cohen's Kappa, respectively. Between all raters, there was poor inter-rater reliability for each round of data collection (κ = .177, κ = .124 for rounds 1 and 2, respectively). Between orthopedic surgeons, there were poor levels of agreement (κ = −.056, κ = .114), whereas, between radiologists, there was fair to moderate agreement (κ = 0.479, κ = 0.340). Within orthopedic raters, κ values ranged from −0.059 to 0.125, indicating, at best, poor intrarater reliability. Within radiologists, κ values ranged from 0.545 to 0.553, indicating moderate agreement within raters. The analysis determined that none of the orthopedic values for inter or intrarater reliability could be deemed statistically different from zero. Overall, classification using MRa resulted in significant disagreement between and within raters. Trained radiologists demonstrated higher overall levels of agreement than orthopedic surgeons. In summary, when using MRa to assess SLAP lesions, Snyder and Maffet classification demonstrates poor reliability by orthopedic surgeons and moderate reliability when used by musculoskeletal radiologists.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,509
Score d'incertitude au seuil0,985

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,034
Tête enseignante GPT0,349
Écart entre enseignants0,315 · 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.

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

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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