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The Bone & Joint Journal
Vol. 106-B, Issue 7 | Pages 646 - 655
1 Jul 2024
Longo UG Gulotta LV De Salvatore S Lalli A Bandini B Giannarelli D Denaro V

Aims

Proximal humeral fractures are the third most common fracture among the elderly. Complications associated with fixation include screw perforation, varus collapse, and avascular necrosis of the humeral head. To address these challenges, various augmentation techniques to increase medial column support have been developed. There are currently no recent studies that definitively establish the superiority of augmented fixation over non-augmented implants in the surgical treatment of proximal humeral fractures. The aim of this systematic review and meta-analysis was to compare the outcomes of patients who underwent locking-plate fixation with cement augmentation or bone-graft augmentation versus those who underwent locking-plate fixation without augmentation for proximal humeral fractures.

Methods

The search was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Articles involving patients with complex proximal humeral fractures treated using open reduction with locking-plate fixation, with or without augmentation, were considered. A meta-analysis of comparative studies comparing locking-plate fixation with cement augmentation or with bone-graft augmentation versus locking-plate fixation without augmentation was performed.


The Bone & Joint Journal
Vol. 104-B, Issue 12 | Pages 1292 - 1303
1 Dec 2022
Polisetty TS Jain S Pang M Karnuta JM Vigdorchik JM Nawabi DH Wyles CC Ramkumar PN

Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered.

Cite this article: Bone Joint J 2022;104-B(12):1292–1303.


The Bone & Joint Journal
Vol. 102-B, Issue 5 | Pages 556 - 567
1 May 2020
Park JW Lee Y Lee YJ Shin S Kang Y Koo K

Deep gluteal syndrome is an increasingly recognized disease entity, caused by compression of the sciatic or pudendal nerve due to non-discogenic pelvic lesions. It includes the piriformis syndrome, the gemelli-obturator internus syndrome, the ischiofemoral impingement syndrome, and the proximal hamstring syndrome. The concept of the deep gluteal syndrome extends our understanding of posterior hip pain due to nerve entrapment beyond the traditional model of the piriformis syndrome. Nevertheless, there has been terminological confusion and the deep gluteal syndrome has often been undiagnosed or mistaken for other conditions. Careful history-taking, a physical examination including provocation tests, an electrodiagnostic study, and imaging are necessary for an accurate diagnosis.

After excluding spinal lesions, MRI scans of the pelvis are helpful in diagnosing deep gluteal syndrome and identifying pathological conditions entrapping the nerves. It can be conservatively treated with multidisciplinary treatment including rest, the avoidance of provoking activities, medication, injections, and physiotherapy.

Endoscopic or open surgical decompression is recommended in patients with persistent or recurrent symptoms after conservative treatment or in those who may have masses compressing the sciatic nerve.

Many physicians remain unfamiliar with this syndrome and there is a lack of relevant literature. This comprehensive review aims to provide the latest information about the epidemiology, aetiology, pathology, clinical features, diagnosis, and treatment.

Cite this article: Bone Joint J 2020;102-B(5):556–567.