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10.1111/tbed.13651 http://scihub22266oqcxt.onion/10.1111/tbed.13651 32469137!7283685!32469137     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\32469137.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Transbound+Emerg+Dis 2020 ; 67 (6): 2823-2829 Nephropedia Template TP {{tp|p=32469137|t=2020. A novel simple scoring model for predicting severity of patients with SARS-CoV-2 infection |pdf=|usr=}}{{32469137}} gab.com Text A novel simple scoring model for predicting severity of patients with SARS-CoV-2 infection JO: Transbound Emerg Dis http://www.kidney.de/pget.php?&tw=1&pmid=32469137 #FOAvip An outbreak of pneumonia caused by a novel coronavirus (COVID-19) began in Wuhan, China in December 2019 and quickly spread throughout the country and world. An efficient and convenient method based on clinical characteristics was needed to evaluate the potential deterioration in patients. We aimed to develop a simple and practical risk scoring system to predict the severity of COVID-19 patients on admission. We retrospectively investigated the clinical information of confirmed COVID-19 patients from 10 February 2020 to 29 February 2020 in Wuhan Union Hospital. Predictors of severity were identified by univariate and multivariate logistic regression analysis. A total of 147 patients with confirmed SARS-CoV-2 infection were grouped into non-severe (94 patients) and severe (53 patients) groups. We found that an increased level of white blood cells (WBC), neutrophils, D-dimer, fibrinogen (FIB), IL-6, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alpha-hydroxybutyrate dehydrogenase (HBDH), serum amyloid A (SAA) and a decreased level of lymphocytes were important risk factors associated with severity. Furthermore, three variables were used to formulate a clinical risk scoring system named COVID-19 index = 3 x D-dimer (microg/L) + 2 x lgESR (mm/hr) - 4 x lymphocyte (x10(9) /L) + 8. The area under the receiver operating characteristic (ROC) curve was 0.843 (95% CI, 0.771-0.914). We propose an effective scoring system to predict the severity of COVID-19 patients. This simple prediction model may provide healthcare workers with a practical method and could positively impact decision-making with regard to deteriorating patients. Twit Text FOAVip A novel simple scoring model for predicting severity of patients with SARS-CoV-2 infection ????Transbound Emerg Dis http://www.kidney.de/pget.php?&tw=1&pmid=32469137 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32469137 #FOAvip English Wikipedia <ref>{{Cite pmid|32469137}}</ref> A novel simple scoring model for predicting severity of patients with SARS-CoV-2 infection #MMPMID32469137 Dong Y; Zhou H; Li M; Zhang Z; Guo W; Yu T; Gui Y; Wang Q; Zhao L; Luo S; Fan H; Hu D Transbound Emerg Dis 2020[Nov]; 67 (6): 2823-2829 PMID32469137show ga An outbreak of pneumonia caused by a novel coronavirus (COVID-19) began in Wuhan, China in December 2019 and quickly spread throughout the country and world. An efficient and convenient method based on clinical characteristics was needed to evaluate the potential deterioration in patients. We aimed to develop a simple and practical risk scoring system to predict the severity of COVID-19 patients on admission. We retrospectively investigated the clinical information of confirmed COVID-19 patients from 10 February 2020 to 29 February 2020 in Wuhan Union Hospital. Predictors of severity were identified by univariate and multivariate logistic regression analysis. A total of 147 patients with confirmed SARS-CoV-2 infection were grouped into non-severe (94 patients) and severe (53 patients) groups. We found that an increased level of white blood cells (WBC), neutrophils, D-dimer, fibrinogen (FIB), IL-6, C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), alanine aminotransferase (ALT), aspartate aminotransferase (AST), alpha-hydroxybutyrate dehydrogenase (HBDH), serum amyloid A (SAA) and a decreased level of lymphocytes were important risk factors associated with severity. Furthermore, three variables were used to formulate a clinical risk scoring system named COVID-19 index = 3 x D-dimer (microg/L) + 2 x lgESR (mm/hr) - 4 x lymphocyte (x10(9) /L) + 8. The area under the receiver operating characteristic (ROC) curve was 0.843 (95% CI, 0.771-0.914). We propose an effective scoring system to predict the severity of COVID-19 patients. This simple prediction model may provide healthcare workers with a practical method and could positively impact decision-making with regard to deteriorating patients. |*Severity of Illness Index[MESH] |Adult[MESH] |Aged[MESH] |COVID-19/*epidemiology/virology[MESH] |China/epidemiology[MESH] |Female[MESH] |Humans[MESH] |Male[MESH] |Middle Aged[MESH] |Models, Theoretical[MESH] |Retrospective Studies[MESH] |Risk Factors[MESH]A novel simple scoring model for predicting severity of patients with (epmc).pdf DeepDyve Pubget Overpricing