The coronavirus disease-2019 (COVID-19) pandemic has affected different sectors of society, and healthcare workers have been particularly impacted. This study aimed to describe the clinical, epidemiological, and molecular characteristics of SARS-CoV-2 infections among healthcare workers in Evandro Chagas Institute, a research reference center in Brazil, from October 2020 to July 2022. 845 samples were collected from individuals who presented clinical symptoms of respiratory infection. Nasopharyngeal positive samples were submitted through genome sequencing. Clinical, epidemiological, and the SARS-CoV-2 lineages (or variants) were analyzed. SARS-CoV-2 positivity was detected in 31.8% (269/845) of samples with a higher prevalence of females (60.2%). The highest SARS-CoV-2 positivity rates were reported in March 2021 (39%), January 2022 (65%), and July 2022 (56%). On clinical symptoms, arthralgia, chills, and diarrhea were statistically significantly detected in 2020; fever, runny nose, and arthralgia in 2021; runny nose, and cough in 2022. On molecular analysis of SARS-CoV-2, 66 samples (25.3%, 66/269) were sequenced and the most prevalent lineage was the Omicron, representing 57.6%. Studies on the epidemiological and clinical characteristics of HCW are essential to propose control measures and work management since research centers play a major role in surveillance to identify and monitor infectious diseases.
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http://dx.doi.org/10.1007/s42770-024-01557-x | DOI Listing |
Sci Rep
December 2024
Department of Biochemistry and Molecular Biology, Medical University of Lublin, 20-093, Lublin, Poland.
Using Fourier Transform Infrared spectroscopy (FTIR), it is possible to show chemical composition of materials and / or profile chemical changes occurring in tissues, cells, and body fluids during onset and progression of diseases. For diagnostic application, the use of blood would be the most appropriate in biospectroscopy studies since, (i) it is easily accessible and, (ii) enables frequent analyses of biochemical changes occurring in pathological states. At present, different studies have investigated potential of serum, plasma and sputum being alternative biofluids for lung cancer detection using FTIR.
View Article and Find Full Text PDFNPJ Vaccines
December 2024
Department for Evidence-based Medicine and Evaluation, University for Continuing Education Krems (Danube University Krems), Krems, Austria.
Pneumococcal infections are a serious health issue associated with increased morbidity and mortality. This systematic review evaluated the efficacy, effectiveness, immunogenicity, and safety of the pneumococcal conjugate vaccine (PCV)15 compared to other pneumococcal vaccines or no vaccination in children and adults. We identified 20 randomized controlled trials (RCTs).
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December 2024
Medical Image Analysis, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high costs. Accurate biomarkers for response are lacking. The present work is the first to investigate the value of deep learning on CT imaging of metastatic lesions for predicting ICI treatment outcomes in advanced melanoma.
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December 2024
Department of Comprehensive Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.
Sacubitril/valsartan, a first-in-class angiotensin receptor neprilysin inhibitor, is widely used to treat heart failure. Despite its efficacy, sacubitril/valsartan inevitably causes adverse events such as hypotension, renal dysfunction, hyperkalemia, and angioedema. Sacubitril/valsartan-associated ototoxicity is often underreported in clinical studies and real-world settings.
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December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
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