Objective We conducted this study to evaluate the reproducibility of a new classification system for Blount's disease and assess its correlation with established radiological measures used to evaluate the severity of this disorder. Materials and Methods This is a retrospective review of children with Blount's disease that were younger than 10 years of age. Recurrence was defined as the need for a second corrective surgery. Radiographs immediately pre-surgery and at final follow-up were used to measure mechanical axis (MA), tibial metaphyseal-diaphyseal angle (TMDA), epiphyseal-metaphyseal angle (EMA), lateral distal femoral angle (LDFA), and medial proximal tibial angle (MPTA). Patients were stratified according to the new classification (Type A, B, or C). Results Sixty-five limbs from 16 males and 24 females met our inclusion criteria. The average follow-up was 4.2 years. Twelve patients (with 22 Type-A extremities) underwent bracing with a success rate of 54%. Thirty-four patients (53 extremities) underwent surgical correction. The recurrence rate was 35.8%. Group C had a recurrence rate of 62%, higher than that of Group B (33%), and Group A (23%) (P = 0.026). In addition, irrespective of reoperation, patients in Group C had the least change in the MA (62%, P = 0.046) and the most severe values of MPTA and TMDA initially and after the operation (P < 0.05). Conclusion The new classification system for Blount's disease holds validity for predicting recurrence. The severity of the grades is correlated with the TMDA, MPTA, and varus reversibility. This can aid physicians and families in making an informed decision and setting treatment goals.
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http://dx.doi.org/10.7759/cureus.8353 | DOI Listing |
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Infectious Disease Consultant, North Potomac, Maryland, USA.
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Hengyang Key Laboratory of Hemorrhagic Cerebrovascular Disease, Department of Neurosurgery, the Second Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, 421000, Hunan, China.
Patients with intracranial aneurysms (IA) undergoing endovascular treatment face varying risks and benefits when tirofiban is used for thromboprophylaxis during surgery. Currently, there is a lack of high-level evidence summarizing this information. This study aims to conduct a systematic review and meta-analysis to evaluate the efficacy and safety of tirofiban during endovascular treatment of IA.
View Article and Find Full Text PDFZ Gerontol Geriatr
January 2025
Geriatrie, Universität Witten-Herdecke, Alfred Herrhausenstraße 50, 58455, Witten, Germany.
Chronic obstructive pulmonary disease (COPD) is a frequent disease from which approximately 8% of individuals aged 40 years and above suffer. The prevalence increases up to fivefold as age advances. Following an introduction including the etiology, measurement, characteristic features and classification of COPD, this article presents the consensus recommendations of the German Working Group on Pneumology in Older Patients.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, National Clinical Research Center for Eye Disease, Shanghai, 200080, China.
The objectives of this study are to construct a deep convolutional neural network (DCNN) model to diagnose and classify meibomian gland dysfunction (MGD) based on the in vivo confocal microscope (IVCM) images and to evaluate the performance of the DCNN model and its auxiliary significance for clinical diagnosis and treatment. We extracted 6643 IVCM images from the three hospitals' IVCM database as the training set for the DCNN model and 1661 IVCM images from the other two hospitals' IVCM database as the test set to examine the performance of the model. Construction of the DCNN model was performed using DenseNet-169.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
Vision transformer (ViT)and convolutional neural networks (CNNs) each possess distinct strengths in medical imaging: ViT excels in capturing long-range dependencies through self-attention, while CNNs are adept at extracting local features via spatial convolution filters. While ViT may struggle with capturing detailed local spatial information, critical for tasks like anomaly detection in medical imaging, shallow CNNs often fail to effectively abstract global context. This study aims to explore and evaluate hybrid architectures that integrate ViT and CNN to leverage their complementary strengths for enhanced performance in medical vision tasks, such as segmentation, classification, reconstruction, and prediction.
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