Background The purpose of this study was to determine the current trends and common practices for the treatment of Kienböck disease at different stages. Question/Purpose To determine the current trends and common practices by hand surgeons for the treatment of Kienböck disease. Methods A survey with hypothetical Kienböck disease cases stratified by the Lichtman staging system was distributed to the American Society for Surgery of the Hand (ASSH) members. Questions and responses reflected common treatment strategies. Results Of a total of 375 worldwide respondents, preferred treatments of Kienböck disease were as follows: for Stage I disease, an initial trial of splinting was favored (74%), followed by radial shortening osteotomy for continued symptoms. For Stage II disease, 63% of surgeons preferred surgical intervention, particularly radial shortening osteotomy. For Stage IIIa with negative ulnar variance, 69% chose radial shortening osteotomy. Responses were heterogeneous for Stage IIIa Kienböck with positive variance, and capitate shortening osteotomy and vascularized bone grafting were preferred. Salvage procedures predominated for Stage IIIb disease, including proximal row carpectomy (PRC; 42%), intracarpal arthrodesis (21%), and total wrist fusion (10.7%). Similarly, Stage IV disease was treated by 87% of respondents by either PRC or wrist fusion. Without regard to stage of disease, 90% of participants reported using the same Lichtman staging to guide treatment and would also alter treatment strategy based upon ulnar variance. Conclusions Most respondents used Lichtman staging and ulnar variance to guide treatment decisions. Results indicate that the most common surgical treatments were radial shortening osteotomy for early disease and PRC in later stages. Level of Evidence Level IV, Economic/Decision Analysis.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4327716 | PMC |
http://dx.doi.org/10.1055/s-0035-1544225 | DOI Listing |
EBioMedicine
January 2025
Division of Liver Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. Electronic address:
Rev Esp Patol
January 2025
Department of Pathology, Vardhman Mahavir Medical College and Safdarjung Hospital, New Delhi, India.
Background: Sarcoidosis, a granulomatous inflammatory disease, exhibits diverse clinical manifestations, often affecting multiple organs. Diagnostic challenges arise due to its similarities with tuberculosis, particularly in high-burden areas. Differentiating between the two relies on clinical judgment, laboratory tests, imaging, and invasive procedures.
View Article and Find Full Text PDFInt J Med Inform
January 2025
School of Geography and the Environment, University of Oxford, South Parks Road, Oxford OX1 3QY, United Kingdom. Electronic address:
Background: Coronavirus Disease 2019 (COVID-19), caused by the SARS-CoV-2 virus, emerged as a global health crisis in 2019, resulting in widespread morbidity and mortality. A persistent challenge during the pandemic has been the accuracy of reported epidemic data, particularly in underdeveloped regions with limited access to COVID-19 test kits and healthcare infrastructure. In the post-COVID era, this issue remains crucial.
View Article and Find Full Text PDFInt J Med Inform
January 2025
Rheumatology and Allergy Clinical Epidemiology Research Center and Division of Rheumatology, Allergy, and Immunology, and Mongan Institute, Department of Medicine, Massachusetts General Hospital Boston MA USA. Electronic address:
Background: ANCA-associated vasculitis (AAV) is a rare but serious disease. Traditional case-identification methods using claims data can be time-intensive and may miss important subgroups. We hypothesized that a deep learning model analyzing electronic health records (EHR) can more accurately identify AAV cases.
View Article and Find Full Text PDFJMIR Form Res
January 2025
Department of Medical and Clinical Psychology, Center of Research on Psychological Disorders and Somatic Diseases (CoRPS), Tilburg University, Tilburg, the Netherlands, 31 134662142.
Background: Health-related data from technological devices are increasingly obtained through smartphone apps and wearable devices. These data could enable physicians and other care providers to monitor patients outside the clinic or assist individuals in improving lifestyle factors. However, the use of health technology data might be hampered by the reluctance of patients to share personal health technology data because of the privacy sensitivity of this information.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!