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10.1002/jmv.26082 http://scihub22266oqcxt.onion/10.1002/jmv.26082 32470186!7283752!32470186     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 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 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 300.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Med+Virol 2020 ; 92 (11): 2616-2622 Nephropedia Template TP {{tp|p=32470186|t=2020. Correlation between the variables collected at admission and progression to severe cases during hospitalization among patients with COVID-19 in Chongqing |pdf=|usr=}}{{32470186}} gab.com Text Correlation between the variables collected at admission and progression to severe cases during hospitalization among patients with COVID-19 in Chongqing JO: J Med Virol http://www.kidney.de/pget.php?&tw=1&pmid=32470186 #FOAvip Mortality is high among severe patients with 2019 novel coronavirus-infected disease (COVID-19). Early prediction of progression to severe cases is needed. We retrospectively collected patients with COVID-19 in two hospital of Chongqing from 1st January to 29th February 2020. At admission, we collected the demographics and laboratory tests to predict whether the patient would progress to severe cases in hospitalization. Severe case was confirmed when one of the following criteria occurred: (a) dyspnea, respiratory rate >/=30 breaths/min, (b) blood oxygen saturation </=93%, and (c) PaO(2) /FiO(2) </= 300 mm Hg. At admission, 348 mild cases were enrolled in this study. Of them, 20 (5.7%) patients progressed to severe cases after median 4.0 days (interquartile range: 2.3-6.0). Pulmonary inflammation index, platelet counts, sodium, C-reactive protein, prealbumin, and PaCO(2) showed good distinguishing power to predict progression to severe cases (each area under the curve of receiver operating characteristics [AUC] >/= 0.8). Age, heart rate, chlorine, alanine aminotransferase, aspartate aminotransferase, procalcitonin, creatine kinase, pH, CD3 counts, and CD4 counts showed moderate distinguishing power (each AUC between 0.7-0.8). And potassium, creatinine, temperature, and D-dimer showed mild distinguishing power (each AUC between 0.6-0.7). In addition, higher C-reactive protein was associated with shorter time to progress to severe cases (r = -0.62). Several easily obtained variables at admission are associated with progression to severe cases during hospitalization. These variables provide a reference for the medical staffs when they manage the patients with COVID-19. Twit Text FOAVip Correlation between the variables collected at admission and progression to severe cases during hospitalization among patients with COVID-19 in Chongqing ????J Med Virol http://www.kidney.de/pget.php?&tw=1&pmid=32470186 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32470186 #FOAvip English Wikipedia <ref>{{Cite pmid|32470186}}</ref> Correlation between the variables collected at admission and progression to severe cases during hospitalization among patients with COVID-19 in Chongqing #MMPMID32470186 Duan J; Wang X; Chi J; Chen H; Bai L; Hu Q; Han X; Hu W; Zhu L; Wang X; Li Y; Zhou C; Mou H; Yan X; Guo S J Med Virol 2020[Nov]; 92 (11): 2616-2622 PMID32470186show ga Mortality is high among severe patients with 2019 novel coronavirus-infected disease (COVID-19). Early prediction of progression to severe cases is needed. We retrospectively collected patients with COVID-19 in two hospital of Chongqing from 1st January to 29th February 2020. At admission, we collected the demographics and laboratory tests to predict whether the patient would progress to severe cases in hospitalization. Severe case was confirmed when one of the following criteria occurred: (a) dyspnea, respiratory rate >/=30 breaths/min, (b) blood oxygen saturation /= 0.8). Age, heart rate, chlorine, alanine aminotransferase, aspartate aminotransferase, procalcitonin, creatine kinase, pH, CD3 counts, and CD4 counts showed moderate distinguishing power (each AUC between 0.7-0.8). And potassium, creatinine, temperature, and D-dimer showed mild distinguishing power (each AUC between 0.6-0.7). In addition, higher C-reactive protein was associated with shorter time to progress to severe cases (r = -0.62). Several easily obtained variables at admission are associated with progression to severe cases during hospitalization. These variables provide a reference for the medical staffs when they manage the patients with COVID-19. |*Severity of Illness Index[MESH] |Adult[MESH] |Aged[MESH] |C-Reactive Protein/analysis[MESH] |COVID-19/*diagnosis/mortality[MESH] |China/epidemiology[MESH] |Comorbidity[MESH] |Disease Progression[MESH] |Female[MESH] |Hospitalization/*statistics & numerical data[MESH] |Humans[MESH] |Male[MESH] |Middle Aged[MESH] |Platelet Count/statistics & numerical data[MESH] |ROC Curve[MESH] |Retrospective Studies[MESH]Correlation between the variables collected at admission and progressi(epmc).pdf DeepDyve Pubget Overpricing