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10.1093/ofid/ofaa169 http://scihub22266oqcxt.onion/10.1093/ofid/ofaa169 32490031!7239104!32490031     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 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 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Open+Forum+Infect+Dis 2020 ; 7 (5): ofaa169 Nephropedia Template TP {{tp|p=32490031|t=2020. Differentiating Between 2019 Novel Coronavirus Pneumonia and Influenza Using a Nonspecific Laboratory Marker-Based Dynamic Nomogram |pdf=|usr=}}{{32490031}} gab.com Text Differentiating Between 2019 Novel Coronavirus Pneumonia and Influenza Using a Nonspecific Laboratory Marker-Based Dynamic Nomogram JO: Open Forum Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=32490031 #FOAvip BACKGROUND: There is currently a lack of nonspecific laboratory indicators as a quantitative standard to distinguish between the 2019 coronavirus disease (COVID-19) and an influenza A or B virus infection. Thus, the aim of this study was to establish a nomogram to detect COVID-19. METHODS: A nomogram was established using data collected from 457 patients (181 with COVID-19 and 276 with influenza A or B infection) in China. The nomogram used age, lymphocyte percentage, and monocyte count to differentiate COVID-19 from influenza. RESULTS: Our nomogram predicted probabilities of COVID-19 with an area under the receiver operating characteristic curve of 0.913 (95% confidence interval [CI], 0.883-0.937), greater than that of the lymphocyte:monocyte ratio (0.849; 95% CI, 0.812-0.880; P = .0007), lymphocyte percentage (0.808; 95% CI, 0.768-0.843; P < .0001), monocyte count (0.780; 95% CI, 0.739-0.817; P < .0001), or age (0.656; 95% CI, 0.610-0.699; P < .0001). The predicted probability conformed to the real observation outcomes of COVID-19, according to the calibration curves. CONCLUSIONS: We found that age, lymphocyte percentage, and monocyte count are risk factors for the early-stage prediction of patients infected with the 2019 novel coronavirus. As such, our research provides a useful test for doctors to differentiate COVID-19 from influenza. Twit Text FOAVip Differentiating Between 2019 Novel Coronavirus Pneumonia and Influenza Using a Nonspecific Laboratory Marker-Based Dynamic Nomogram ????Open Forum Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=32490031 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32490031 #FOAvip English Wikipedia <ref>{{Cite pmid|32490031}}</ref> Differentiating Between 2019 Novel Coronavirus Pneumonia and Influenza Using a Nonspecific Laboratory Marker-Based Dynamic Nomogram #MMPMID32490031 Wang L; Liu Y; Zhang T; Jiang Y; Yang S; Xu Y; Song R; Song M; Wang L; Zhang W; Han B; Yang L; Fan Y; Cheng C; Wang J; Xiang P; Pu L; Xiong H; Li C; Zhang M; Tan J; Chen Z; Liu J; Wang X Open Forum Infect Dis 2020[May]; 7 (5): ofaa169 PMID32490031show ga BACKGROUND: There is currently a lack of nonspecific laboratory indicators as a quantitative standard to distinguish between the 2019 coronavirus disease (COVID-19) and an influenza A or B virus infection. Thus, the aim of this study was to establish a nomogram to detect COVID-19. METHODS: A nomogram was established using data collected from 457 patients (181 with COVID-19 and 276 with influenza A or B infection) in China. The nomogram used age, lymphocyte percentage, and monocyte count to differentiate COVID-19 from influenza. RESULTS: Our nomogram predicted probabilities of COVID-19 with an area under the receiver operating characteristic curve of 0.913 (95% confidence interval [CI], 0.883-0.937), greater than that of the lymphocyte:monocyte ratio (0.849; 95% CI, 0.812-0.880; P = .0007), lymphocyte percentage (0.808; 95% CI, 0.768-0.843; P < .0001), monocyte count (0.780; 95% CI, 0.739-0.817; P < .0001), or age (0.656; 95% CI, 0.610-0.699; P < .0001). The predicted probability conformed to the real observation outcomes of COVID-19, according to the calibration curves. CONCLUSIONS: We found that age, lymphocyte percentage, and monocyte count are risk factors for the early-stage prediction of patients infected with the 2019 novel coronavirus. As such, our research provides a useful test for doctors to differentiate COVID-19 from influenza. äDifferentiating Between 2019 Novel Coronavirus Pneumonia and Influenza(epmc).pdf DeepDyve Pubget Overpricing