Auscultation of the lung remains an essential part of physical examination even though its limitations, particularly with regard to communicating subjective findings, are well recognised. The European Respiratory Society (ERS) Task Force on Respiratory Sounds was established to build a reference collection of audiovisual recordings of lung sounds that should aid in the standardisation of nomenclature. Five centres contributed recordings from paediatric and adult subjects. Based on pre-defined quality criteria, 20 of these recordings were selected to form the initial reference collection. All recordings were assessed by six observers and their agreement on classification, using currently recommended nomenclature, was noted for each case. Acoustical analysis was added as supplementary information. The audiovisual recordings and related data can be accessed online in the ERS e-learning resources. The Task Force also investigated the current nomenclature to describe lung sounds in 29 languages in 33 European countries. Recommendations for terminology in this report take into account the results from this survey.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1183/13993003.01132-2015 | DOI Listing |
Diabetes Care
January 2025
Rutgers Robert Wood Johnson Medical School, New Brunswick, NJ.
Objective: We derive and validate D-RISK, an electronic health record (EHR)-driven risk score to optimize and facilitate screening for undiagnosed dysglycemia (prediabetes + diabetes) in clinical practice.
Research Design And Methods: We used retrospective EHR data (derivation sample) and a prospective diabetes screening study (validation sample) to develop D-RISK. Logistic regression with backward selection was used to predict dysglycemia (HbA1c ≥5.
Learn Health Syst
January 2025
Introduction: Like many other academic medical centers, the University of Alabama at Birmingham (UAB) aspires to adopt learning health system (LHS) principles and practices more fully. Applying LHS principles establishes a culture where clinical and operational practices constantly generate questions and leverage information technology (IT) and methodological expertise to facilitate systematic evaluation of care delivery, health outcomes, and the effects of improvement initiatives. Despite the potential benefits, differences in priorities, timelines, and expectations spanning an academic medical center's clinical care, administrative operations, and research arms create barriers to adopting and implementing an LHS.
View Article and Find Full Text PDFAlzheimers Dement (N Y)
January 2025
Indiana Alzheimer Disease Research Center and Center for Neuroimaging, Department of Radiology and Imaging Sciences Indiana University School of Medicine Indianapolis Indiana USA.
Introduction: The exponential growth of genomic datasets necessitates advanced analytical tools to effectively identify genetic loci from large-scale high throughput sequencing data. This study presents Deep-Block, a multi-stage deep learning framework that incorporates biological knowledge into its AI architecture to identify genetic regions as significantly associated with Alzheimer's disease (AD). The framework employs a three-stage approach: (1) genome segmentation based on linkage disequilibrium (LD) patterns, (2) selection of relevant LD blocks using sparse attention mechanisms, and (3) application of TabNet and Random Forest algorithms to quantify single nucleotide polymorphism (SNP) feature importance, thereby identifying genetic factors contributing to AD risk.
View Article and Find Full Text PDFAlzheimers Dement (Amst)
January 2025
Introduction: Studies have shown that blood biomarkers can differentiate dementia disorders. However, the diagnosis of dementia still relies primarily on cerebrospinal fluid and imaging modalities. The new disease-modifying treatments call for more widely applicable biomarkers.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!