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10.1080/21505594.2020.1840108 http://scihub22266oqcxt.onion/10.1080/21505594.2020.1840108 33172355!7671095!33172355     free     free     free Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 235.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Virulence 2020 ; 11 (1): 1569-1581 Nephropedia Template TP {{tp|p=33172355|t=2020. Novel biomarkers for the prediction of COVID-19 progression a retrospective, multi-center cohort study |pdf=|usr=}}{{33172355}} gab.com Text Novel biomarkers for the prediction of COVID-19 progression a retrospective, multi-center cohort study JO: Virulence http://www.kidney.de/pget.php?&tw=1&pmid=33172355 #FOAvip A pandemic designated as Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading worldwide. Up to date, there is no efficient biomarker for the timely prediction of the disease progression in patients. To analyze the inflammatory profiles of COVID-19 patients and demonstrate their implications for the illness progression of COVID-19. Retrospective analysis of 3,265 confirmed COVID-19 cases hospitalized between 10 January 2020, and 26 March 2020 in three medical centers in Wuhan, China. Patients were diagnosed as COVID-19 and hospitalized in Leishenshan Hospital, Zhongnan Hospital of Wuhan University and The Seventh Hospital of Wuhan, China. Univariable and multivariable logistic regression models were used to determine the possible risk factors for disease progression. Moreover, cutoff values, the sensitivity and specificity of inflammatory parameters for disease progression were determined by MedCalc Version 19.2.0. Age (95%CI, 1.017 to 1.048; P < 0.001), serum amyloid A protein (SAA) (95%CI, 1.216 to 1.396; P < 0.001) and erythrocyte sedimentation rate (ESR) (95%CI, 1.006 to 1.045; P < 0.001) were likely the risk factors for the disease progression. The Area under the curve (AUC) of SAA for the progression of COVID-19 was 0.923, with the best predictive cutoff value of SAA of 12.4 mg/L, with a sensitivity of 83.9% and a specificity of 97.67%. SAA-containing parameters are novel promising ones for predicting disease progression in COVID-19. Twit Text FOAVip Novel biomarkers for the prediction of COVID-19 progression a retrospective, multi-center cohort study ????Virulence http://www.kidney.de/pget.php?&tw=1&pmid=33172355 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33172355 #FOAvip English Wikipedia <ref>{{Cite pmid|33172355}}</ref> Novel biomarkers for the prediction of COVID-19 progression a retrospective, multi-center cohort study #MMPMID33172355 Yu Y; Liu T; Shao L; Li X; He CK; Jamal M; Luo Y; Wang Y; Liu Y; Shang Y; Pan Y; Wang X; Zhou F Virulence 2020[Dec]; 11 (1): 1569-1581 PMID33172355show ga A pandemic designated as Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading worldwide. Up to date, there is no efficient biomarker for the timely prediction of the disease progression in patients. To analyze the inflammatory profiles of COVID-19 patients and demonstrate their implications for the illness progression of COVID-19. Retrospective analysis of 3,265 confirmed COVID-19 cases hospitalized between 10 January 2020, and 26 March 2020 in three medical centers in Wuhan, China. Patients were diagnosed as COVID-19 and hospitalized in Leishenshan Hospital, Zhongnan Hospital of Wuhan University and The Seventh Hospital of Wuhan, China. Univariable and multivariable logistic regression models were used to determine the possible risk factors for disease progression. Moreover, cutoff values, the sensitivity and specificity of inflammatory parameters for disease progression were determined by MedCalc Version 19.2.0. Age (95%CI, 1.017 to 1.048; P < 0.001), serum amyloid A protein (SAA) (95%CI, 1.216 to 1.396; P < 0.001) and erythrocyte sedimentation rate (ESR) (95%CI, 1.006 to 1.045; P < 0.001) were likely the risk factors for the disease progression. The Area under the curve (AUC) of SAA for the progression of COVID-19 was 0.923, with the best predictive cutoff value of SAA of 12.4 mg/L, with a sensitivity of 83.9% and a specificity of 97.67%. SAA-containing parameters are novel promising ones for predicting disease progression in COVID-19. |Aged[MESH] |Area Under Curve[MESH] |Betacoronavirus/genetics/*isolation & purification[MESH] |Biomarkers[MESH] |Blood Sedimentation[MESH] |C-Reactive Protein/analysis[MESH] |COVID-19[MESH] |China[MESH] |Cohort Studies[MESH] |Coronavirus Infections/*diagnosis[MESH] |Disease Progression[MESH] |Female[MESH] |Humans[MESH] |Larynx/virology[MESH] |Leukocyte Count[MESH] |Logistic Models[MESH] |Male[MESH] |Middle Aged[MESH] |Pandemics[MESH] |Pneumonia, Viral/*diagnosis[MESH] |Predictive Value of Tests[MESH] |RNA, Viral/isolation & purification[MESH] |Real-Time Polymerase Chain Reaction[MESH] |Retrospective Studies[MESH] |Risk Factors[MESH] |SARS-CoV-2[MESH] |Sensitivity and Specificity[MESH]Novel biomarkers for the prediction of COVID-19 progression a retrospe(epmc).pdf DeepDyve Pubget Overpricing