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Bone & Joint Open
Vol. 2, Issue 7 | Pages 552 - 561
28 Jul 2021
Werthel J Boux de Casson F Burdin V Athwal GS Favard L Chaoui J Walch G

Aims. The aim of this study was to describe a quantitative 3D CT method to measure rotator cuff muscle volume, atrophy, and balance in healthy controls and in three pathological shoulder cohorts. Methods. In all, 102 CT scans were included in the analysis: 46 healthy, 21 cuff tear arthropathy (CTA), 18 irreparable rotator cuff tear (IRCT), and 17 primary osteoarthritis (OA). The four rotator cuff muscles were manually segmented and their volume, including intramuscular fat, was calculated. The normalized volume (NV) of each muscle was calculated by dividing muscle volume to the patient’s scapular bone volume. Muscle volume and percentage of muscle atrophy were compared between muscles and between cohorts. Results. Rotator cuff muscle volume was significantly decreased in patients with OA, CTA, and IRCT compared to healthy patients (p < 0.0001). Atrophy was comparable for all muscles between CTA, IRCT, and OA patients, except for the supraspinatus, which was significantly more atrophied in CTA and IRCT (p = 0.002). In healthy shoulders, the anterior cuff represented 45% of the entire cuff, while the posterior cuff represented 40%. A similar partition between anterior and posterior cuff was also found in both CTA and IRCT patients. However, in OA patients, the relative volume of the anterior (42%) and posterior cuff (45%) were similar. Conclusion. This study shows that rotator cuff muscle volume is significantly decreased in patients with OA, CTA, or IRCT compared to healthy patients, but that only minimal differences can be observed between the different pathological groups. This suggests that the influence of rotator cuff muscle volume and atrophy (including intramuscular fat) as an independent factor of outcome may be overestimated. Cite this article: Bone Jt Open 2021;2(7):552–561


Bone & Joint Open
Vol. 3, Issue 12 | Pages 977 - 990
23 Dec 2022
Latijnhouwers D Pedersen A Kristiansen E Cannegieter S Schreurs BW van den Hout W Nelissen R Gademan M

Aims

This study aimed to investigate the estimated change in primary and revision arthroplasty rate in the Netherlands and Denmark for hips, knees, and shoulders during the COVID-19 pandemic in 2020 (COVID-period). Additional points of focus included the comparison of patient characteristics and hospital type (2019 vs COVID-period), and the estimated loss of quality-adjusted life years (QALYs) and impact on waiting lists.

Methods

All hip, knee, and shoulder arthroplasties (2014 to 2020) from the Dutch Arthroplasty Register, and hip and knee arthroplasties from the Danish Hip and Knee Arthroplasty Registries, were included. The expected number of arthroplasties per month in 2020 was estimated using Poisson regression, taking into account changes in age and sex distribution of the general Dutch/Danish population over time, calculating observed/expected (O/E) ratios. Country-specific proportions of patient characteristics and hospital type were calculated per indication category (osteoarthritis/other elective/acute). Waiting list outcomes including QALYs were estimated by modelling virtual waiting lists including 0%, 5% and 10% extra capacity.


Bone & Joint Open
Vol. 3, Issue 4 | Pages 291 - 301
4 Apr 2022
Holleyman RJ Lyman S Bankes MJK Board TN Conroy JL McBryde CW Andrade AJ Malviya A Khanduja V

Aims

This study uses prospective registry data to compare early patient outcomes following arthroscopic repair or debridement of the acetabular labrum.

Methods

Data on adult patients who underwent arthroscopic labral debridement or repair between 1 January 2012 and 31 July 2019 were extracted from the UK Non-Arthroplasty Hip Registry. Patients who underwent microfracture, osteophyte excision, or a concurrent extra-articular procedure were excluded. The EuroQol five-dimension (EQ-5D) and International Hip Outcome Tool 12 (iHOT-12) questionnaires were collected preoperatively and at six and 12 months post-operatively. Due to concerns over differential questionnaire non-response between the two groups, a combination of random sampling, propensity score matching, and pooled multivariable linear regression models were employed to compare iHOT-12 improvement.