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Identification of threshold pathoanatomic metrics in primary glenohumeral osteoarthritis.
Gauci, Marc-Olivier; Athwal, George S; Sanchez-Sotelo, Joaquin; Chaoui, Jean; Urvoy, Manuel; Boileau, Pascal; Walch, Gilles.
Afiliação
  • Gauci MO; Institut Universitaire Locomoteur & Sport, Unité de Recherche Clinique Côte d'Azur (UR2CA), Hôpital Pasteur 2, Université Côte d'Azur, Nice, France. Electronic address: marcoliviergauci@gmail.com.
  • Athwal GS; St Joseph's Health Care London, London, Ontario, Canada.
  • Sanchez-Sotelo J; Department of Orthopaedic Surgery, Mayo Clinic, Rochester, MN, USA.
  • Chaoui J; Société IMASCAP, Plouzané, France.
  • Urvoy M; Société IMASCAP, Plouzané, France.
  • Boileau P; Institut Universitaire Locomoteur & Sport, Unité de Recherche Clinique Côte d'Azur (UR2CA), Hôpital Pasteur 2, Université Côte d'Azur, Nice, France.
  • Walch G; Hôpital Privé Jean Mermoz-Generale De Santé (GDS) Ramsay, Lyon, France.
J Shoulder Elbow Surg ; 30(10): 2270-2282, 2021 Oct.
Article em En | MEDLINE | ID: mdl-33813011
ABSTRACT

BACKGROUND:

An assessment of the pathoanatomic parameters of the arthritic glenohumeral joint (GHJ) has the potential to identify discriminating metrics to differentiate glenoid types in shoulders with primary glenohumeral osteoarthritis (PGHOA). The aim was to identify the morphometric differences and threshold values between glenoid types including normal and arthritic glenoids with the various types in the Walch classification. We hypothesized that there would be clear morphometric discriminators between the various glenoid types and that specific numeric threshold values would allow identification of each glenoid type.

METHODS:

The computed tomography scans of 707 shoulders were analyzed 585 obtained from shoulders with PGHOA and 122 from shoulders without glenohumeral pathology. Glenoid morphology was classified according to the Walch classification. All computed tomography scans were imported in a dedicated automatic 3D-software program that referenced measurements to the scapular body plane. Glenoid and humeral modeling was performed using the best-fit sphere method, and the root-mean-square error was calculated. The direction and orientation of the glenoid and humerus described glenohumeral relationships.

RESULTS:

Among shoulders with PGHOA, 90% of the glenoids and 85% of the humeral heads were directed posteriorly in reference to the scapular body plane. Several discriminatory pathoanatomic parameters were identified GHJ narrowing < 3 mm was a discriminatory metric for type A glenoids. Posterior humeral subluxation > 70% discriminated type B1 from normal GHJs. The root-mean-square error was a discriminatory metric to distinguish type B2 from type A, type B3, and normal GHJs. Type B3 glenoids differed from type A2 by greater retroversion (>13°) and subluxation (>71%). The type C glenoid retroversion inferior limit was 21°, whereas normal glenoids never presented with retroversion > 16°.

CONCLUSION:

Pathoanatomic metrics with the identified threshold values can be used to discriminate glenoid types in shoulders with PGHOA.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Osteoartrite / Articulação do Ombro Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: J Shoulder Elbow Surg Assunto da revista: ORTOPEDIA Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Osteoartrite / Articulação do Ombro Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: J Shoulder Elbow Surg Assunto da revista: ORTOPEDIA Ano de publicação: 2021 Tipo de documento: Article