Humeral Head Morphometry Can Predict the Presence of Subacromial Spurs: Measurements of Dried Bones from Human Shoulder Girdles.


Journal

The Tokai journal of experimental and clinical medicine
ISSN: 2185-2243
Titre abrégé: Tokai J Exp Clin Med
Pays: Japan
ID NLM: 7704186

Informations de publication

Date de publication:
20 Apr 2019
Historique:
received: 12 11 2018
accepted: 25 12 2018
entrez: 10 4 2019
pubmed: 10 4 2019
medline: 8 5 2019
Statut: epublish

Résumé

To clarify the relationship between the morphological characteristics of the bones of the shoulder girdle and the presence of subacromial spurs (SS). The bones of 36 cadaveric shoulder girdles were measured. After dividing the bone specimens into SS present and absent groups, various bone parameters between the two groups were statistically compared. Logistic regression analysis was conducted to assess the significance of each parameter as a predictor of SS formation. A receiver operating characteristic curve analysis was used to determine the cut-off point and to assess the sensitivity and specificity of the parameters showing significant differences. SS were found in 16 scapulae. The values for five parameters of the examined shoulder girdles were significantly different between the two groups. The presence of SS depended on the humeral head ratio, which was calculated by dividing the length of the greater tubercle of the humerus by the length of the lesser tubercle. A cut-off value of 1.97 was suitable for discriminating between the presence and absence of SS (sensitivity, 75%; specificity, 80%). The presence of SS is related to several morphological characteristics of the shoulder girdle and, the presence of SS can be predicted using humeral head morphometry.

Identifiants

pubmed: 30963523

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

9-14

Auteurs

Shogo Hayashi (S)

Department of Anatomy, School of Medicine, International University of Health and Welfare, 4-3 Kozunomori, Narita, Chiba 286-8686, Japan. sho5-884@umin.ac.jp.

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Classifications MeSH