Background And Purpose: The stroke subtype, Oxfordshire Community Stroke Project classification, age, and prestroke modified Rankin (SOAR) score is a prognostic scale proposed for early mortality prediction after acute stroke. We aimed to evaluate whether including a measure of initial stroke severity (National Institutes of Health Stroke Scale and modified-SOAR [mSOAR] scores) would improve the prognostic accuracy.
Methods: Using Anglia Stroke and Heart Clinical Network data, 2008 to 2011, we assessed the performance of SOAR and mSOAR against in-hospital mortality using area under the receiver operating curve statistics. We externally validated the prognostic utility of SOAR and mSOAR using an independent cohort data set from Glasgow. We described calibration using Hosmer-Lemeshow goodness-of-fit test.
Results: A total of 1002 patients were included in the derivation cohort, and 105 (10.5%) died as inpatients. The area under the receiver operating curves for outcome of early mortality derived from the SOAR and mSOAR scores were 0.79 (95% confidence interval, 0.75-0.84) and 0.83 (95% confidence interval, 0.79-0.86), respectively (P=0.001). The external validation data set contained 1012 patients with stroke; of which, 121 (12.0%) patients died within 90 days. The mSOAR scores identified the risk of early mortality ranging from 3% to 42%. External validation of mSOAR score yielded an area under the receiver operating curve of 0.84 (95% confidence interval, 0.82-0.88) for outcome of early mortality. Calibration was good (P=0.70 for the Hosmer-Lemeshow test).
Conclusions: Adding National Institutes of Health Stroke Scale data to create a modified-SOAR score improved prognostic utility in both derivation and validation data sets. The mSOAR may have clinical utility by using easily available data to predict mortality.
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http://dx.doi.org/10.1161/STROKEAHA.115.009898 | DOI Listing |
BMC Pulm Med
January 2025
Department of Key Laboratory of Ningxia Stem Cell and Regenerative Medicine, Institute of Medical Sciences, Department of Pulmonary and Critical Care Medicine, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, 750004, China.
Background: In this study, we aimed to explore the association between baseline and early changes in the neutrophil-to-lymphocyte ratio (NLR) and the 30-day mortality rate in patients having anti-melanoma differentiation-associated gene 5 (MDA5)-positive dermatomyositis with interstitial lung disease (DM-ILD).
Methods: Overall, 263 patients with anti-MDA5 DM-ILD from four centers in China were analyzed. Multivariate logistic regression analysis was used to evaluate the impact of baseline NLR on the 30-day mortality rate in patients with anti-MDA5-positive DM-ILD.
J Interv Card Electrophysiol
January 2025
Division of Cardiology, Northwestern University, Chicago, IL, USA.
Atrial arrhythmias, including atrial fibrillation (AF), are a major contributor to cardiovascular morbidity and mortality. Early detection and effective management are critical to mitigating adverse outcomes such as stroke, heart failure, and overall mortality. Wearable devices have emerged as promising tools for monitoring, detecting, and managing atrial arrhythmias near-continuously.
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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 PDFBMJ Open
January 2025
Centre for Cancer Screening, Prevention and Early Diagnosis, Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Background: Worldwide, lung cancer (LC) is the second most frequent cancer and the leading cause of cancer related mortality. Low-dose CT (LDCT) screening reduced LC mortality by 20-24% in randomised trials of high-risk populations. A significant proportion of those screened have nodules detected that are found to be benign.
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