Objective: Displaced ipsilateral fractures of the clavicle and the glenoid neck are usually the result of high-energy trauma. The objective of this study is to evaluate the association of the glenopolar angle (GPA) with the clinical outcome of the floating shoulders.
Methods: Seven patients treated conservatively and nine patients with clavicular fracture treated operatively were evaluated retrospectively. The GPA of the affected (a-GPA) and unaffected (u-GPA) shoulders, and the change (d-GPA) were measured. The Constant-Murley score of the affected (a-CS) and unaffected (u-CS) shoulders, and the change (d-CS) were measured at the last follow-up.
Results: The mean follow-up was 25 months, and the score was 69.7 points. Patient age had no effect on the clinical outcome, and the change in GPA in the affected shoulder between the initial and last follow-up for the nonoperated and operated groups did not differ statistically (p > 0.05). There were positive correlations between a-CS and a-GPA (r = 0.760, p < 0.05) and between d-GPA and d-CS (r = 0.643, p < 0.05) and negative correlations between a-GPA and d-CS (r = -0.962, p < 0.05) and between d-GPA and a-CS (r = -0.703, p < 0.05).
Conclusion: The simple measurement of GPA may yield useful prognostic information and help in making decisions concerning the floating shoulder.
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http://dx.doi.org/10.1097/01.ta.0000240982.99842.b9 | DOI Listing |
Cureus
July 2024
Anatomy, All India Institute of Medical Sciences, Patna, Patna, IND.
Background: The glenopolar angle (GPA), usually ranges from 30° to 45°. GPA measures the tilt of the plane of the glenoid cavity in relation to the axis of the body of the scapula passing from the superior pole of the glenoid cavity to the inferior angle of the scapula. It is essential to assess the results of surgeries for dislocated shoulders.
View Article and Find Full Text PDFPLoS One
July 2024
Orthopedic Surgery Department, Upper Limb Surgery Unit, "San Cecilio" University Hospital of Granada, Madrid, Spain.
Eur J Radiol
August 2024
ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland. Electronic address:
Objectives: To develop and validate an open-source deep learning model for automatically quantifying scapular and glenoid morphology using CT images of normal subjects and patients with glenohumeral osteoarthritis.
Materials And Methods: First, we used deep learning to segment the scapula from CT images and then to identify the location of 13 landmarks on the scapula, 9 of them to establish a coordinate system unaffected by osteoarthritis-related changes, and the remaining 4 landmarks on the glenoid cavity to determine the glenoid size and orientation in this scapular coordinate system. The glenoid version, glenoid inclination, critical shoulder angle, glenopolar angle, glenoid height, and glenoid width were subsequently measured in this coordinate system.
Medeni Med J
March 2024
Bursa Uludag University Faculty of Medicine, Department of Anatomy, Bursa, Turkey.
Medeni Med J
March 2024
Banaras Hindu University, Institute of Medical Sciences, Department of Anatomy, Varanasi, India.
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