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Bone & Joint Research
Vol. 12, Issue 8 | Pages 455 - 466
1 Aug 2023
Zhou H Chen C Hu H Jiang B Yin Y Zhang K Shen M Wu S Wang Z

Aims. Rotator cuff muscle atrophy and fatty infiltration affect the clinical outcomes of rotator cuff tear patients. However, there is no effective treatment for fatty infiltration at this time. High-intensity interval training (HIIT) helps to activate beige adipose tissue. The goal of this study was to test the role of HIIT in improving muscle quality in a rotator cuff tear model via the β3 adrenergic receptor (β3AR). Methods. Three-month-old C57BL/6 J mice underwent a unilateral rotator cuff injury procedure. Mice were forced to run on a treadmill with the HIIT programme during the first to sixth weeks or seventh to 12th weeks after tendon tear surgery. To study the role of β3AR, SR59230A, a selective β3AR antagonist, was administered to mice ten minutes before each exercise through intraperitoneal injection. Supraspinatus muscle, interscapular brown fat, and inguinal subcutaneous white fat were harvested at the end of the 12th week after tendon tear and analyzed biomechanically, histologically, and biochemically. Results. Histological analysis of supraspinatus muscle showed that HIIT improved muscle atrophy, fatty infiltration, and contractile force compared to the no exercise group. In the HIIT groups, supraspinatus muscle, interscapular brown fat, and inguinal subcutaneous white fat showed increased expression of tyrosine hydroxylase and uncoupling protein 1, and upregulated the β3AR thermogenesis pathway. However, the effect of HIIT was not present in mice injected with SR59230A, suggesting that HIIT affected muscles via β3AR. Conclusion. HIIT improved supraspinatus muscle quality and function after rotator cuff tears by activating systemic sympathetic nerve fibre near adipocytes and β3AR. Cite this article: Bone Joint Res 2023;12(8):455–466


Bone & Joint Research
Vol. 12, Issue 3 | Pages 165 - 177
1 Mar 2023
Boyer P Burns D Whyne C

Aims. An objective technological solution for tracking adherence to at-home shoulder physiotherapy is important for improving patient engagement and rehabilitation outcomes, but remains a significant challenge. The aim of this research was to evaluate performance of machine-learning (ML) methodologies for detecting and classifying inertial data collected during in-clinic and at-home shoulder physiotherapy exercise. Methods. A smartwatch was used to collect inertial data from 42 patients performing shoulder physiotherapy exercises for rotator cuff injuries in both in-clinic and at-home settings. A two-stage ML approach was used to detect out-of-distribution (OOD) data (to remove non-exercise data) and subsequently for classification of exercises. We evaluated the performance impact of grouping exercises by motion type, inclusion of non-exercise data for algorithm training, and a patient-specific approach to exercise classification. Algorithm performance was evaluated using both in-clinic and at-home data. Results. The patient-specific approach with engineered features achieved the highest in-clinic performance for differentiating physiotherapy exercise from non-exercise activity (area under the receiver operating characteristic (AUROC) = 0.924). Including non-exercise data in algorithm training further improved classifier performance (random forest, AUROC = 0.985). The highest accuracy achieved for classifying individual in-clinic exercises was 0.903, using a patient-specific method with deep neural network model extracted features. Grouping exercises by motion type improved exercise classification. For at-home data, OOD detection yielded similar performance with the non-exercise data in the algorithm training (fully convolutional network AUROC = 0.919). Conclusion. Including non-exercise data in algorithm training improves detection of exercises. A patient-specific approach leveraging data from earlier patient-supervised sessions should be considered but is highly dependent on per-patient data quality. Cite this article: Bone Joint Res 2023;12(3):165–177


Bone & Joint Research
Vol. 10, Issue 2 | Pages 113 - 121
1 Feb 2021
Nicholson JA Oliver WM MacGillivray TJ Robinson CM Simpson AHRW

Aims

To evaluate if union of clavicle fractures can be predicted at six weeks post-injury by the presence of bridging callus on ultrasound.

Methods

Adult patients managed nonoperatively with a displaced mid-shaft clavicle were recruited prospectively. Ultrasound evaluation of the fracture was undertaken to determine if sonographic bridging callus was present. Clinical risk factors at six weeks were used to stratify patients at high risk of nonunion with a combination of Quick Disabilities of the Arm, Shoulder and Hand questionnaire (QuickDASH) ≥ 40, fracture movement on examination, or absence of callus on radiograph.


Bone & Joint Research
Vol. 2, Issue 7 | Pages 132 - 139
1 Jul 2013
Ketola S Lehtinen J Rousi T Nissinen M Huhtala H Konttinen YT Arnala I

Objectives

To report the five-year results of a randomised controlled trial examining the effectiveness of arthroscopic acromioplasty in the treatment of stage II shoulder impingement syndrome.

Methods

A total of 140 patients were randomly divided into two groups: 1) supervised exercise programme (n = 70, exercise group); and 2) arthroscopic acromioplasty followed by a similar exercise programme (n = 70, combined treatment group).