Background: In December 2019, SARS-COV-2 infection emerged in Wuhan, China causing COVID-19 and subsequently spread throughout the globe. A great uncertainty is associated with the disease progression, as the risk of severe COVID-19 is not uniform among all the patients. Systemic inflammation has been reported as a predictor for COVID-19 outcomes. Elevated levels of inflammatory markers are shown to be associated with endothelial dysfunction, cytokine storm and coagulopathy in COVID-19. There is a growing body of evidence, that these findings exert influence in the causation of mortality in patients with severe Covid-19. The present study is carried out with an aim to evaluate the clinical outcomes of patients by interrelating their clinical severity with inflammatory markers and CT (Computed tomography) severity score (CTSS).
Objectives: The aim of the study is to correlate COVID-19 severity with inflammatory markers and CT severity score. We also aim to determine the optimal cut-off values for inflammatory markers and CT severity scores in order to establish their interrelationship to the disease severity.
Materials And Methods: It is a hospital-based retrospective observational study. The study was conducted over a period of four months (July 2020 to October 2020) based on data obtained from the records of patients, admitted with a laboratory confirmed SARS-COV-2 infection. The current study included a total of 84 patients, admitted to ICU with the severe COVID-19.Study tools included serum CRP, serum ferritin, D-dimer, neutrophil-to-lymphocyte ratio (NLR), interleukin-6 (IL-6) and 25-point CT severity score obtained from HRCT (high resolution computerized tomography) chest.
Results: Out of 84 patients recruited, 54 patients were survivors and 30 patients were non-survivors (deceased). 78% of the study population was male and 22% was female. For survivors, average CTSS was 12.43 ± 5.7 and whereas average CTSS for non-survivors was 18.87 ± 4.68(p<0001). Average D-dimer was 2.5 ± 1.43 in the survivor group and 3.39 ± 0.95 for non-survivors (p<0.004). Correlation coefficient of CTSS with FiO2 is 0.685 (p<0.0001). The optimal cut-off value for predicting mortality for D-dimer is >2.4 (p<0.0012) and for CTSS is >15 (p<0.0001).
Conclusion: The disease severity was significantly correlated with CTSS and D- dimer. Severe COVID-19 was also associated with a high NLR (neutrophil to lymphocyte ratio) and moderately elevated inflammatory markers (CRP, Ferritin, IL-6). CTSS >15 and D-dimer >2.4 correlate strongly with mortality. CTSS has the greatest diagnostic accuracy for stratifying the disease severity and predicting the mortality among the markers/ characteristics compared.
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Hepatology
January 2025
Université Côte d'Azur, INSERM, U1065, C3M, Nice, France.
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Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States.
Bone mineral density (BMD), an important marker of bone health, is regulated by a complex interaction of proteins. Plasma proteomic analyses can contribute to identification of proteins associated with changes in BMD. This may be especially informative in stages of bone accrual and peak BMD achievement (i.
View Article and Find Full Text PDFPLoS One
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Institute of Sport Sciences, Jerzy Kukuczka Academy of Physical Education in Katowice, Katowice, Poland.
Curcumin is known for its potential health benefits; however, the evidence remains inconclusive regarding its necessity as a supplement for athletes during the preparatory phase of training. This study aimed to assess the effect of 6-week curcumin supplementation at a dose of 2g/day on selected inflammatory markers, blood count, and brain-derived neurotropic factor (BDNF) levels in middle-aged amateur long-distance runners during the preparatory period of a macrocycle. Thirty runners were randomly assigned to either a curcumin-supplemented group (CUR, n = 15) or a placebo group (PLA, n = 15).
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Department of Internal Medicine-Cardiovascular, Guangzhou Twelfth People's Hospital, No.1, Tianqiang Road, Tianhe District, Guangzhou City, Guangdong Province, 510620, China.
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