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Intensive Care Risk Estimation in COVID-19 Pneumonia Based on Clinical and Imaging Parameters: Experiences from the Munich Cohort |pdf=|usr=}}{{32443442}} gab.com Text Intensive Care Risk Estimation in COVID-19 Pneumonia Based on Clinical and Imaging Parameters: Experiences from the Munich Cohort JO: J Clin Med http://www.kidney.de/pget.php?&tw=1&pmid=32443442 #FOAvip The evolving dynamics of coronavirus disease 2019 (COVID-19) and the increasing infection numbers require diagnostic tools to identify patients at high risk for a severe disease course. Here we evaluate clinical and imaging parameters for estimating the need of intensive care unit (ICU) treatment. We collected clinical, laboratory and imaging data from 65 patients with confirmed COVID-19 infection based on polymerase chain reaction (PCR) testing. Two radiologists evaluated the severity of findings in computed tomography (CT) images on a scale from 1 (no characteristic signs of COVID-19) to 5 (confluent ground glass opacities in over 50% of the lung parenchyma). The volume of affected lung was quantified using commercially available software. Machine learning modelling was performed to estimate the risk for ICU treatment. Patients with a severe course of COVID-19 had significantly increased interleukin (IL)-6, C-reactive protein (CRP), and leukocyte counts and significantly decreased lymphocyte counts. The radiological severity grading was significantly increased in ICU patients. Multivariate random forest modelling showed a mean +/- standard deviation sensitivity, specificity and accuracy of 0.72 +/- 0.1, 0.86 +/- 0.16 and 0.80 +/- 0.1 and a receiver operating characteristic-area under curve (ROC-AUC) of 0.79 +/- 0.1. The need for ICU treatment is independently associated with affected lung volume, radiological severity score, CRP, and IL-6. Twit Text FOAVip Intensive Care Risk Estimation in COVID-19 Pneumonia Based on Clinical and Imaging Parameters: Experiences from the Munich Cohort ????J Clin Med http://www.kidney.de/pget.php?&tw=1&pmid=32443442 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32443442 #FOAvip English Wikipedia <ref>{{Cite pmid|32443442}}</ref> Intensive Care Risk Estimation in COVID-19 Pneumonia Based on Clinical and Imaging Parameters: Experiences from the Munich Cohort #MMPMID32443442 Burian E; Jungmann F; Kaissis GA; Lohofer FK; Spinner CD; Lahmer T; Treiber M; Dommasch M; Schneider G; Geisler F; Huber W; Protzer U; Schmid RM; Schwaiger M; Makowski MR; Braren RF J Clin Med 2020[May]; 9 (5): ä PMID32443442show ga The evolving dynamics of coronavirus disease 2019 (COVID-19) and the increasing infection numbers require diagnostic tools to identify patients at high risk for a severe disease course. Here we evaluate clinical and imaging parameters for estimating the need of intensive care unit (ICU) treatment. We collected clinical, laboratory and imaging data from 65 patients with confirmed COVID-19 infection based on polymerase chain reaction (PCR) testing. Two radiologists evaluated the severity of findings in computed tomography (CT) images on a scale from 1 (no characteristic signs of COVID-19) to 5 (confluent ground glass opacities in over 50% of the lung parenchyma). The volume of affected lung was quantified using commercially available software. Machine learning modelling was performed to estimate the risk for ICU treatment. Patients with a severe course of COVID-19 had significantly increased interleukin (IL)-6, C-reactive protein (CRP), and leukocyte counts and significantly decreased lymphocyte counts. The radiological severity grading was significantly increased in ICU patients. Multivariate random forest modelling showed a mean +/- standard deviation sensitivity, specificity and accuracy of 0.72 +/- 0.1, 0.86 +/- 0.16 and 0.80 +/- 0.1 and a receiver operating characteristic-area under curve (ROC-AUC) of 0.79 +/- 0.1. The need for ICU treatment is independently associated with affected lung volume, radiological severity score, CRP, and IL-6. äIntensive Care Risk Estimation in COVID-19 Pneumonia Based on Clinical(epmc).pdf DeepDyve Pubget Overpricing