Background: We modified our treatment algorithm for proximal humeral fractures in elderly patients in 2013 to a more conservative approach avoiding locking plates. This study assesses the impact of this change on patient self-dependence.
Methods: We carried out an observational comparative study including both retrospectively and prospectively collected data. For the former, 147 isolated proximal humeral fracture patients older than 65 years were treated between 2011 and 2013 at our hospital and included in a historical group. The revised treatment algorithm was applied in a similar non-concurrent, comparative patient group (n = 160) prospectively enrolled between 2015 and 2017. The primary outcome was any loss of self-dependence, with secondary outcomes including documentation of shoulder functional scores, quality of life, and adverse events.
Results: Historical and prospective patients had similar baseline characteristics. Nonoperative treatment was performed in 53 historical patients (36%) and 83 prospective patients (78%). Prospective patients were 1.6 times less likely to lose some level of self-dependence (risk ratio, 0.62; 95% confidence interval, 0.25-1.5; P = .292), and the local adverse event risk dropped from 12.2% to 5.7% (P = .078). Mean shoulder function and quality of life were similar between the 2 groups.
Conclusion: By applying our revised algorithm, a higher proportion of elderly patients maintained their premorbid level of self-dependence and returned to their previous social environment.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.jse.2019.11.006 | DOI Listing |
Sci Rep
January 2025
Department of Electrical Electronical Engineering, Yaşar University, Bornova, İzmir, Turkey.
We aimed to build a robust classifier for the MGMT methylation status of glioblastoma in multiparametric MRI. We focused on multi-habitat deep image descriptors as our basic focus. A subset of the BRATS 2021 MGMT methylation dataset containing both MGMT class labels and segmentation masks was used.
View Article and Find Full Text PDFSci Rep
January 2025
School of Computing, SASTRA Deemed University, Thanjavur, Tamil Nadu, India.
Mechanical ventilation is the process through which breathing support is provided to patients who face inconvenience during respiration. During the pandemic, many people were suffering from lung disorders, which elevated the demand for mechanical ventilators. The handling of mechanical ventilators is to be done under the assistance of trained professionals and demands the selection of ideal parameters.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Oncology, The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.
Exploring the potential of advanced artificial intelligence technology in predicting microsatellite instability (MSI) and Ki-67 expression of endometrial cancer (EC) is highly significant. This study aimed to develop a novel hybrid radiomics approach integrating multiparametric magnetic resonance imaging (MRI), deep learning, and multichannel image analysis for predicting MSI and Ki-67 status. A retrospective study included 156 EC patients who were subsequently categorized into MSI and Ki-67 groups.
View Article and Find Full Text PDFSci Rep
January 2025
College of Information Science and Technology, Hainan Normal University, Haikou, 571158, China.
Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for reducing mortality rates and ensuring timely treatment. Computer-aided diagnosis systems provide automated mammography image processing, interpretation, and grading. However, since the currently existing methods suffer from such issues as overfitting, lack of adaptability, and dependence on massive annotated datasets, the present work introduces a hybrid approach to enhance breast cancer classification accuracy.
View Article and Find Full Text PDFSci Rep
January 2025
Faculty of Engineering, Université de Moncton, Moncton, NB, E1A3E9, Canada.
Diabetes is a growing health concern in developing countries, causing considerable mortality rates. While machine learning (ML) approaches have been widely used to improve early detection and treatment, several studies have shown low classification accuracies due to overfitting, underfitting, and data noise. This research employs parallel and sequential ensemble ML approaches paired with feature selection techniques to boost classification accuracy.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!