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10.1002/jmv.25969 http://scihub22266oqcxt.onion/10.1002/jmv.25969 32369205!7267495!32369205     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Med+Virol 2020 ; 92 (10): 2074-2080 Nephropedia Template TP {{tp|p=32369205|t=2020. Individualized prediction nomograms for disease progression in mild COVID-19 |pdf=|usr=}}{{32369205}} gab.com Text Individualized prediction nomograms for disease progression in mild COVID-19 JO: J Med Virol http://www.kidney.de/pget.php?&tw=1&pmid=32369205 #FOAvip The coronavirus disease 2019 (COVID-19) has evolved into a pandemic rapidly. The majority of COVID-19 patients are with mild syndromes. This study aimed to develop models for predicting disease progression in mild cases. The risk factors for the requirement of oxygen support in mild COVID-19 were explored using multivariate logistic regression. Nomogram as visualization of the models was developed using R software. A total of 344 patients with mild COVID-19 were included in the final analysis, 45 of whom progressed and needed high-flow oxygen therapy or mechanical ventilation after admission. There were 188 (54.7%) males, and the average age of the cohort was 52.9 +/- 16.8 years. When the laboratory data were not included in multivariate analysis, diabetes, coronary heart disease, T >/= 38.5? and sputum were independent risk factors of progressive COVID-19 (Model 1). When the blood routine test was included the CHD, T >/= 38.5? and neutrophil-to-lymphocyte ratio were found to be independent predictors (Model 2). The area under the receiver operator characteristic curve of model 2 was larger than model 1 (0.872 vs 0.849, P = .023). The negative predictive value of both models was greater than 96%, indicating they could serve as simple tools for ruling out the possibility of disease progression. In conclusion, two models comprised common symptoms (fever and sputum), underlying diseases (diabetes and coronary heart disease) and blood routine test are developed for predicting the future requirement of oxygen support in mild COVID-19 cases. Twit Text FOAVip Individualized prediction nomograms for disease progression in mild COVID-19 ????J Med Virol http://www.kidney.de/pget.php?&tw=1&pmid=32369205 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32369205 #FOAvip English Wikipedia <ref>{{Cite pmid|32369205}}</ref> Individualized prediction nomograms for disease progression in mild COVID-19 #MMPMID32369205 Huang J; Cheng A; Lin S; Zhu Y; Chen G J Med Virol 2020[Oct]; 92 (10): 2074-2080 PMID32369205show ga The coronavirus disease 2019 (COVID-19) has evolved into a pandemic rapidly. The majority of COVID-19 patients are with mild syndromes. This study aimed to develop models for predicting disease progression in mild cases. The risk factors for the requirement of oxygen support in mild COVID-19 were explored using multivariate logistic regression. Nomogram as visualization of the models was developed using R software. A total of 344 patients with mild COVID-19 were included in the final analysis, 45 of whom progressed and needed high-flow oxygen therapy or mechanical ventilation after admission. There were 188 (54.7%) males, and the average age of the cohort was 52.9 +/- 16.8 years. When the laboratory data were not included in multivariate analysis, diabetes, coronary heart disease, T >/= 38.5? and sputum were independent risk factors of progressive COVID-19 (Model 1). When the blood routine test was included the CHD, T >/= 38.5? and neutrophil-to-lymphocyte ratio were found to be independent predictors (Model 2). The area under the receiver operator characteristic curve of model 2 was larger than model 1 (0.872 vs 0.849, P = .023). The negative predictive value of both models was greater than 96%, indicating they could serve as simple tools for ruling out the possibility of disease progression. In conclusion, two models comprised common symptoms (fever and sputum), underlying diseases (diabetes and coronary heart disease) and blood routine test are developed for predicting the future requirement of oxygen support in mild COVID-19 cases. |COVID-19/*pathology/virology[MESH] |Disease Progression[MESH] |Female[MESH] |Humans[MESH] |Lymphocytes/pathology[MESH] |Male[MESH] |Middle Aged[MESH] |Multivariate Analysis[MESH] |Neutrophils/pathology[MESH] |Pandemics[MESH] |Pneumonia, Viral/pathology/virology[MESH] |ROC Curve[MESH] |Retrospective Studies[MESH] |Risk Factors[MESH]Individualized prediction nomograms for disease progression in mild CO(epmc).pdf DeepDyve Pubget Overpricing