Eighty-six mucous cysts in 79 patients were surgically excised. Follow-up was carried out at an average of 2.6 years. Fifteen digits (17%) had a residual loss of extension of 5 to 20 degrees at the IP or DIP joints. One patient developed a superficial infection and two developed a DIP pyarthrosis, which eventually required DIP arthrodesis. Nail deformities were present in 25 of 86 digits preoperatively (29%), 15 of which resolved after surgery (60%). Four of 61 digits developed a nail deformity which was not present preoperatively (7%). Three of 86 digits (3%) developed recurrence. Other complications included persistent swelling, pain, numbness, stiffness, and radial or ulnar deviation at the DIP joint. We recommend that patients be informed preoperatively of the potential risks of decreased range of motion, persistent swelling and pain, infection, recurrence, and persistent or postoperatively acquired nail deformity.
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http://dx.doi.org/10.1016/s0266-7681(97)80067-8 | DOI Listing |
Digital health interventions (DHIs), such as apps, websites and wearables, are being presented as solutions or enablers to manage the burden of cardiometabolic disease in healthcare. However, the potential benefits of DHIs may not be reaching the most in-need populations, who may face intersecting barriers to accessing health services and digital solutions. The Digital Interventions for South Asians in Cardiometabolic Disease (DISC) study used a mixed-method approach to focus on people of a South Asian background, a high-risk group for cardiometabolic disease.
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January 2025
Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, China.
Existing prognostic models are useful for estimating the prognosis of lung adenocarcinoma patients, but there remains room for improvement. In the current study, we developed a deep learning model based on histopathological images to predict the recurrence risk of lung adenocarcinoma patients. The efficiency of the model was then evaluated in independent multicenter cohorts.
View Article and Find Full Text PDFNPJ Digit Med
January 2025
Department of Computer Science and Technology & Institute for Artificial Intelligence & BNRist, Tsinghua University, Beijing, China.
Rare diseases, affecting ~350 million people worldwide, pose significant challenges in clinical diagnosis due to the lack of experienced physicians and the complexity of differentiating between numerous rare diseases. To address these challenges, we introduce PhenoBrain, a fully automated artificial intelligence pipeline. PhenoBrain utilizes a BERT-based natural language processing model to extract phenotypes from clinical texts in EHRs and employs five new diagnostic models for differential diagnoses of rare diseases.
View Article and Find Full Text PDFFront Digit Health
January 2025
Department Organisation and Quality of Care, Netherlands Institute for Health Services Research, Utrecht, Netherlands.
Introduction: The digitalization of healthcare poses a risk of exacerbating health inequalities. Dutch public libraries offer freely accessible e-health courses given by trainers. However, there is limited knowledge on whether these libraries successfully reach and support those in need.
View Article and Find Full Text PDFDigit Health
January 2025
Department of Computer Science, School of Systems and Technology, University of Management and Technology, Lahore, Pakistan.
Objective: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition influenced by various genetic and environmental factors. Currently, there is no definitive clinical test, such as a blood analysis or brain scan, for early diagnosis. The objective of this study is to develop a computational model that predicts ASD driver genes in the early stages using genomic data, aiming to enhance early diagnosis and intervention.
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