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Differential risk of healthcare workers versus the general population during outbreak, war and pandemic crises.
Eur J Epidemiol
November 2024
Departments of Medicine, of Epidemiology and Population Health, of Biomedical Data Science, and of Statistics and Meta-Research Innovation Center at Stanford (METRICS), Stanford University, 1265 Welch Rd, Medical School Office Building, Room X306, Stanford, CA, 94305, USA.
Healthcare workers may have different risk for severe outcomes compared with the general population during diverse crises. This paper introduces the concept of healthcare worker versus population hazard (HPH), the risk of an outcome of interest in active healthcare workers compared with the general population they serve. HPH can be expressed with relative risk (HPH(r)) and absolute risk difference (HPH(a)) metrics.
View Article and Find Full Text PDFHealthcare professionals' knowledge and perceptions of post-stroke rehabilitation in the peripandemic period: an online cross-sectional survey.
Rheumatol Int
December 2024
Department of Physical Medicine and Rehabilitation, University of Health Sciences, Adana Health Practice and Research Center, Adana, Türkiye.
The COVID-19 pandemic has profoundly affected healthcare systems, particularly post-stroke rehabilitation centers. The elevated severity of strokes and delayed hospital admissions caused numerous hurdles to rehabilitation administration during the peri-pandemic period. This study surveyed healthcare professionals' knowledge and perceptions of post-stroke rehabilitation during this period.
View Article and Find Full Text PDFAccurate bacterial outbreak tracing with Oxford Nanopore sequencing and reduction of methylation-induced errors.
Genome Res
November 2024
Institute for Infectious Diseases and Infection Control, Jena University Hospital, 07747 Jena, Germany.
Our study investigates the effectiveness of Oxford Nanopore Technologies for accurate outbreak tracing by resequencing 33 isolates of a 3-year-long outbreak with Illumina short-read sequencing data as the point of reference. We detect considerable base errors through cgMLST and phylogenetic analysis of genomes sequenced with Oxford Nanopore Technologies, leading to the false exclusion of some outbreak-related strains from the outbreak cluster. Nearby methylation sites cause these errors and can also be found in other species besides Based on these data, we explore PCR-based sequencing and a masking strategy, which both successfully address these inaccuracies and ensure accurate outbreak tracing.
View Article and Find Full Text PDFData-driven classification and explainable-AI in the field of lung imaging.
Front Big Data
September 2024
PolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy.
Detecting lung diseases in medical images can be quite challenging for radiologists. In some cases, even experienced experts may struggle with accurately diagnosing chest diseases, leading to potential inaccuracies due to complex or unseen biomarkers. This review paper delves into various datasets and machine learning techniques employed in recent research for lung disease classification, focusing on pneumonia analysis using chest X-ray images.
View Article and Find Full Text PDFManagement of tuberculosis patients and the role of forensic medicine in COVID-19 pandemic.
Indian J Tuberc
October 2024
Department of Microbiology, Jaya College of Arts and Science, Tirunindravur, Chennai, 602024, Tamilnadu, India. Electronic address:
Tuberculosis and Coronaviral disease-19 had a global impact in 2020 and still predominating, both infectious diseases similar to the lethal pandemics spread in one route, likely airborne transmission, the infected person could spread to healthy people. However, tuberculosis slightly varies from COVID-19. Though the primordial disease of the tuberculosis epidemic has had a vast impact on this society, besides the COVID-19 pandemic with other co-morbidities, conditions faced numerous complications.
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