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10.1038/s41598-021-85779-1 http://scihub22266oqcxt.onion/10.1038/s41598-021-85779-1 33742041!7979799!33742041     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sci+Rep 2021 ; 11 (1): 6422 Nephropedia Template TP {{tp|p=33742041|t=2021. Combining initial chest CT with clinical variables in differentiating coronavirus disease 2019 (COVID-19) pneumonia from influenza pneumonia |pdf=|usr=}}{{33742041}} gab.com Text Combining initial chest CT with clinical variables in differentiating coronavirus disease 2019 (COVID-19) pneumonia from influenza pneumonia JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=33742041 #FOAvip Coronavirus disease 2019 (COVID-19) has spread in more than 100 countries and regions around the world, raising grave global concerns. COVID-19 has a similar pattern of infection, clinical symptoms, and chest imaging findings to influenza pneumonia. In this retrospective study, we analysed clinical and chest CT data of 24 patients with COVID-19 and 79 patients with influenza pneumonia. Univariate analysis demonstrated that the temperature, systolic pressure, cough and sputum production could distinguish COVID-19 from influenza pneumonia. The diagnostic sensitivity and specificity for the clinical features are 0.783 and 0.747, and the AUC value is 0.819. Univariate analysis demonstrates that nine CT features, central-peripheral distribution, superior-inferior distribution, anterior-posterior distribution, patches of GGO, GGO nodule, vascular enlargement in GGO, air bronchogram, bronchiectasis within focus, interlobular septal thickening, could distinguish COVID-19 from influenza pneumonia. The diagnostic sensitivity and specificity for the CT features are 0.750 and 0.962, and the AUC value is 0.927. Finally, a multivariate logistic regression model combined the variables from the clinical variables and CT features models was made. The combined model contained six features: systolic blood pressure, sputum production, vascular enlargement in the GGO, GGO nodule, central-peripheral distribution and bronchiectasis within focus. The diagnostic sensitivity and specificity for the combined features are 0.87 and 0.96, and the AUC value is 0.961. In conclusion, some CT features or clinical variables can differentiate COVID-19 from influenza pneumonia. Moreover, CT features combined with clinical variables had higher diagnostic performance. Twit Text FOAVip Combining initial chest CT with clinical variables in differentiating coronavirus disease 2019 (COVID-19) pneumonia from influenza pneumonia ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=33742041 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33742041 #FOAvip English Wikipedia <ref>{{Cite pmid|33742041}}</ref> Combining initial chest CT with clinical variables in differentiating coronavirus disease 2019 (COVID-19) pneumonia from influenza pneumonia #MMPMID33742041 Zhao S; Huang Z; Zeng H; Chen Z; Luo F; Zhang C; Song B Sci Rep 2021[Mar]; 11 (1): 6422 PMID33742041show ga Coronavirus disease 2019 (COVID-19) has spread in more than 100 countries and regions around the world, raising grave global concerns. COVID-19 has a similar pattern of infection, clinical symptoms, and chest imaging findings to influenza pneumonia. In this retrospective study, we analysed clinical and chest CT data of 24 patients with COVID-19 and 79 patients with influenza pneumonia. Univariate analysis demonstrated that the temperature, systolic pressure, cough and sputum production could distinguish COVID-19 from influenza pneumonia. The diagnostic sensitivity and specificity for the clinical features are 0.783 and 0.747, and the AUC value is 0.819. Univariate analysis demonstrates that nine CT features, central-peripheral distribution, superior-inferior distribution, anterior-posterior distribution, patches of GGO, GGO nodule, vascular enlargement in GGO, air bronchogram, bronchiectasis within focus, interlobular septal thickening, could distinguish COVID-19 from influenza pneumonia. The diagnostic sensitivity and specificity for the CT features are 0.750 and 0.962, and the AUC value is 0.927. Finally, a multivariate logistic regression model combined the variables from the clinical variables and CT features models was made. The combined model contained six features: systolic blood pressure, sputum production, vascular enlargement in the GGO, GGO nodule, central-peripheral distribution and bronchiectasis within focus. The diagnostic sensitivity and specificity for the combined features are 0.87 and 0.96, and the AUC value is 0.961. In conclusion, some CT features or clinical variables can differentiate COVID-19 from influenza pneumonia. Moreover, CT features combined with clinical variables had higher diagnostic performance. |Adult[MESH] |COVID-19/*diagnosis/diagnostic imaging[MESH] |Diagnosis, Differential[MESH] |Female[MESH] |Humans[MESH] |Influenza, Human/*diagnosis/diagnostic imaging[MESH] |Male[MESH] |Middle Aged[MESH] |Pneumonia, Viral/*diagnosis/diagnostic imaging[MESH] |Retrospective Studies[MESH] |Thorax/diagnostic imaging[MESH] |Tomography, X-Ray Computed[MESH]Combining initial chest CT with clinical variables in differentiating (epmc).pdf DeepDyve Pubget Overpricing