Normal Glenoid Relationships Used for Unilateral Quantification of Glenoid Bone Loss in Glenohumeral Instability
Notice bibliographique
Résumé
Objectives: Current methods used to quantify glenoid bone loss following anterior shoulder instability rely on bilateral shoulder imaging to obtain normal linear and surface area parameters of the uninjured glenoid fossa. This method is based on the assumption that there is little side-side variability in these anatomical relationships. Previous reports have demonstrated differences in the morphology of the glenoid fossa based on the anterior glenoid notch. The purpose of this study was to determine the normal dimensions of height, width, surface area, and shape of the human glenoid fossa as function of glenoid notch, and to determine if side-to-side differences exist for these parameters. Due to notch variation, we hypothesize that the inferior glenoid fossa is better represented as an ellipse versus a perfect circle as previously described. We also hypothesize that side-to-side differences exist in glenoid surface area. Methods: The authors studied 58 human scapulae pairs between 18 and 35 years of age from the Hamann-Todd Osteological Collection. Age, sex, race, body height and weight were known for each specimen. Paired specimens were sorted into groups of 5 according to race, sex, and notch type. All specimens were digitized using a 3-D laser scanner, with a stated accuracy of 0.005 inches. Height, width, surface area, and notch angle measurements were calculated using software written in the MATLAB platform. A best fit ellipse was applied to the inferior glenoid based on the glenoid circumference below the notch. Differences in surface area of paired glenoids were assessed using a matched pairs T-test. Multiple stepwise linear regression models were created to select predictors of glenoid surface area. Lastly, the intra-rater and inter-rater reliability of the notch classification as reported by Merrill et al. was assessed among 13 raters. Results: The mean height (s.d.) of the glenoid fossae was 35.0 ± 2.8 mm. Inferior width was 24.8 ± 2.5 mm. The best-fit ellipse of the inferior glenoid had a mean eccentricity of 0.425 ± 0.099. The right glenoid, when compared to its left counterpart, had greater overall surface area (x̄ right = 679.6 mm 2 , x̄ left = 657.2 mm 2 , P< 0.0001*) and inferior surface area (x̄ right = 548.2 mm 2 , x̄ left = 533.1 mm 2 , P< 0.0076*). Patient height, sex, and glenoid height correlated with total and inferior glenoid surface area with r 2 = 0.902 and 0.779, respectively (P< 0.0001*). Analysis of intra-observer reliability showed a consistency of 0.56 (95% CI= 0.26- 0.77), while the inter-observer reliability kappa coefficient was 0.43 (95% CI= 0.41- 0.45). Conclusion: By considering unilateral anatomic relationships of the glenoid fossa, we were able to determine alternative methods of evaluating glenoid bone loss. Glenoid notch angle had moderate reliability and was not considered clinically useful to stratify glenoid morphology. Based on non-zero eccentricity values of the best-fit ellipse, the inferior glenoid fossa did not represent a perfect circle. In addition, side-to-side differences were found between glenoid surface area measurements. The latter two findings contradict assumptions made by current techniques used in clinical practice to calculate bone loss and raise concern as to their validity. Using easily obtainable patient (height and sex) and glenoid (height) parameters, glenoid surface area can be predicted by means of regression modeling, permitting unilateral measurements of glenoid bone loss to be made in clinical practice.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».