Background Scapholunate reconstruction poses a challenge to orthopedic surgeons. Materials and Methods Prospective cohort. Description of Technique Our technique for scapholunate (SL) reconstruction involves ligament reconstruction utilizing a portion of the flexor carpi radialis tendon rerouted via transosseous tunnels across the scaphoid, lunate, and triquetrum (scapholunotriquetral tenodesis). The tendon graft is secured with interference screw fixation into the triquetrum. The philosophy of this new technique is to reduce subluxation and maintain the relationship between scaphoid and lunate by placing a graft through the center of the SL articulation. This graft is then tensioned by passing it centrally through the lunate and triquetrum and secured using an interference screw in the triquetrum. Secondary stabilizers, including the dorsal intercarpal ligament, are then augmented by passing the graft back to the scaphoid, crossing from the triquetrum over the proximal capitate. This further reinforces the translational relationship between the scaphoid and the triquetrum and, therefore, augments stability of the SL articulation. Results We have utilized this technique successfully in over 40 patients since 2009. We report on a prospective consecutive series of 11 patients with over 12 months follow-up (range 12 to 24 months) demonstrating good early radiological and clinical outcomes. Conclusions In developing this technique, we aimed to take the best features of previously described techniques and address the perceived shortcomings of each. We believe there are several benefits of our technique. Moreover, few other techniques address as many of the aspects of chronic SL instability as our technique does. Interference screws for cadaveric preliminary investigation were donated by Arthrex Inc.

Musculoskeletal conditions affect an estimated 1.7 billion people worldwide, causing intense pain and disability. These conditions lead to 30 million emergency room visits yearly, and the numbers are only increasing. However, diagnosing musculoskeletal issues can be challenging, especially in emergencies where quick decisions are necessary. Deep learning (DL) has shown promise in various medical applications. However, previous methods had poor performance and a lack of transparency in detecting shoulder abnormalities on X-ray images due to a lack of training data and better representation of features. This often resulted in overfitting, poor generalisation, and potential bias in decision-making. To address these issues, a new trustworthy DL framework has been proposed to detect shoulder abnormalities (such as fractures, deformities, and arthritis) using X-ray images. The framework consists of two parts: same-domain transfer learning (TL) to mitigate imageNet mismatch and feature fusion to reduce error rates and improve trust in the final result. Same-domain TL involves training pre-trained models on a large number of labelled X-ray images from various body parts and fine-tuning them on the target dataset of shoulder X-ray images. Feature fusion combines the extracted features with seven DL models to train several ML classifiers. The proposed framework achieved an excellent accuracy rate of 99.2%, F1_Score of 99.2%, and Cohen’s kappa of 98.5%. Furthermore, the accuracy of the results was validated using three visualisation tools, including gradient-based class activation heat map (Grad CAM), activation visualisation, and locally interpretable model-independent explanations (LIME). The proposed framework outperformed previous DL methods and three orthopaedic surgeons invited to classify the test set, who obtained an average accuracy of 79.1%. The proposed framework has proven effective and robust, improving generalisation and increasing trust in the final results.

Massive irreparable rotator cuff tears are often associated with severe functional impairment and disabling pain. One viable treatment option is a latissimus dorsi tendon transfer. We propose an all‐arthroscopic technique that we believe avoids insult to the deltoid musculature while reducing morbidity from open harvest of the tendon. The operation is performed with the patient in the lateral decubitus position, by use of a combination of viewing and working portals in the axilla. The initial viewing portal is placed along the anterior belly of the latissimus muscle in the axilla. The latissimus and teres major are identified, as is the thoracodorsal neurovascular pedicle. The tendons are carefully separated, and the inferior and superior borders of the latissimus are whipstitched using a suture passer, which helps facilitate subsequent mobilization of the muscle. The interval deep to the deltoid and superficial to the teres minor is developed into a subdeltoid tunnel for arthroscopic tendon transfer. The latissimus tendon is then transferred and stabilized arthroscopically to the supraspinatus footprint with suture anchors. Our preliminary data suggest that this surgical technique results in improvement in pain, range of motion, and function. Technique Video: video See video under supplementary data.

This paper reports the results of fixation of intraarticular fractures of the distal radius using the TriMed fragment-specific fixation system by surgeons early in their experience with the system. A consecutive series of 22 AO types C2 and C3 fractures in 21 patients were internally fixed with the system. Restoration of articular congruity to less than 2 mm was possible in 20 fractures. At a minimum of 6 months follow-up, mean volar and radial inclination were 8° and 25°, respectively, with no loss of reduction. The patients had a mean of 50° flexion, 63° extension and a pronation–supination arc of 149°. The mean subjective Patient Rated Wrist Score was 20. Our complication rate was comparable to other published series despite long operating times. Therefore, we commend the system as a powerful tool to treat these difficult fractures but acknowledge the significant learning curve.

Background: The accuracy of human pose tracking using smartphone camera (2D-pose) to quantify shoulder range of motion (RoM) is not determined. Methods: Twenty healthy individuals were recruited and performed shoulder abduction, adduction, flexion, or extension, captured simultaneously using a smartphone-based human pose estimation algorithm (Apple’s vision framework) and using a skin marker-based 3D motion capture system. Validity was assessed by comparing the 2D-pose outcomes against a well-established 3D motion capture protocol. In addition, the impact of iPhone positioning was investigated using three smartphones in multiple vertical and horizontal positions. The relationship and validity were analysed using linear mixed models and Bland-Altman analysis. Results: We found that 2D-pose-based shoulder RoM was consistent with 3D motion capture (linear mixed model: R² > 0.93) but was somewhat overestimated by the smartphone. Differences were dependent on shoulder movement type and RoM amplitude, with adduction the worst performer among all tested movements. All motion types were described using linear equations. Correction methods are provided to correct potential out-of-plane shoulder movements. Conclusions: Shoulder RoM estimated using a smartphone camera is consistent with 3D motion-capture-derived RoM; however, differences between the systems were observed and are likely explained by differences in thoracic frame definitions.