When and how much does the muscle strength recover after arthroscopic superior capsular reconstruction?

BACKGROUND: Recently, arthroscopic superior capsular reconstruction (SCR) has been performed for irreparable large to massive rotator cuff tears and excellent clinical results have been reported. Although the muscle strength is reported to recover, it has not yet been clarified when and how much it recovers. The purpose of this study was to determine the recovery pattern of muscle strength after SCR. METHODS: We retrospectively reviewed 35 patients (mean age, 65 years) who met the following inclusion criteria: (1) patients with large to massive irreparable tears of the rotator cuff including the supraspinatus and infraspinatus tendons; (2) those with severe muscle atrophy and fatty change; (3) those who underwent assessment of muscle quality and strength by magnetic resonance imaging and dynamometry at 6 months, 1 year, and 2 years; (4) those with a minimum follow-up period of 2 years; and (5) those without severe osteoarthritis. The isometric muscle strength of scaption (ie, scapular-plane elevation), internal rotation, and external rotation in adduction was measured twice for each motion by a dynamometer. RESULTS: Relative to the muscle strength on the uninvolved side, the involved side showed 61% ± 21% in scaption, 63% ± 20% in external rotation, and 103% ± 29% in internal rotation at 2 years after surgery. Whereas no significant differences were observed between the 1-year and 2-year follow-up assessments, a significant difference in muscle strength of scaption was found between 6 months and 1 year (P = .0174). Graft retear was seen in 5 cases (14%). There was a trend that the muscle strength of scaption and external rotation in the no-retear group was greater than that in the retear group despite no significant difference (P = .0717 and P = .0824, respectively). CONCLUSION: The recovery of the muscle strength after SCR was observed until 1 year after surgery, and the muscle strength of scaption and external rotation returned to 60% of that on the uninvolved side at 2 years.

Statistical shape models that predict native glenoid width based on glenoid height are inaccurate in their current form: a cross-sectional study.

BACKGROUND: The extent of measurement errors of statistical shape models that predict native glenoid width based on glenoid height to subsequently determine the amount of anterior glenoid bone loss is unclear. Therefore, the aim of this study was to (1) create a statistical shape model based on glenoid height and width measured on 3-dimensional computed tomography (3D-CT) and determine the accuracy through measurement errors and (2) determine measurement errors of existing 3D-CT statistical shape models. MATERIALS AND METHODS: A retrospective cross-sectional study included all consecutive patients who underwent CT imaging before undergoing primary surgical treatment of traumatic anterior shoulder dislocation between 2007 and 2022 at the Tohoku University Hospital and affiliated hospitals. Patients were included when instability was unilateral and CT scans of both the injured and contralateral uninjured shoulder were available. 3D segmentations were created and glenoid height and width of the injured and contralateral uninjured side (gold standard) were measured. Accuracy was determined through measurement errors, which were defined as a percentage error deviation from native glenoid width (contralateral uninjured glenoid), calculated as follows: measurement error = [(estimated glenoid width with a statistical shape model - native glenoid width) / native glenoid width] × 100%. A linear regression analysis was performed to create a statistical shape model based on glenoid height according to the formula: native glenoid width = a × glenoid height + b. RESULTS: The diagnosis and procedure codes identified 105 patients, of which 69 (66%) were eligible for inclusion. Glenoid height demonstrated a very strong correlation (r = 0.80) with native glenoid width. The linear regression formula based on this cohort was as follows: native glenoid width = 0.75 × glenoid height - 0.61, and it demonstrated an absolute average measurement error of 5% ± 4%. The formulas by Giles et al, Chen et al and Rayes et al demonstrated absolute average measurement errors of 10% ± 7%, 6% ± 5%, and 9% ± 6%, respectively. CONCLUSION: Statistical shape models that estimate native glenoid width based on glenoid height demonstrate unacceptable measurement errors, despite a high correlation. Therefore, great caution is advised when using these models to determine glenoid bone loss percentage. To minimize errors caused by morphologic differences, preference goes to methods that use the contralateral side as reference.