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10.1007/s11739-020-02480-3 http://scihub22266oqcxt.onion/10.1007/s11739-020-02480-3 32930963!7490315!32930963     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Intern+Emerg+Med 2020 ; 15 (8): 1409-1414 Nephropedia Template TP {{tp|p=32930963|t=2020. Derivation and validation of the clinical prediction model for COVID-19 |pdf=|usr=}}{{32930963}} gab.com Text Derivation and validation of the clinical prediction model for COVID-19 JO: Intern Emerg Med http://www.kidney.de/pget.php?&tw=1&pmid=32930963 #FOAvip The epidemic phase of Coronavirus disease 2019 (COVID-19) made the Worldwide health system struggle against a severe interstitial pneumonia requiring high-intensity care settings for respiratory failure. A rationalisation of resources and a specific treatment path were necessary. The study suggests a predictive model drawing on clinical data gathered by 119 consecutive patients with laboratory-confirmed COVID-19 admitted in Busto Arsizio hospital. We derived a score that identifies the risk of clinical evolution and in-hospital mortality clustering patients into four groups. The study outcomes have been compared across the derivation and validation samples. The prediction rule is based on eight simple patient characteristics that were independently associated with study outcomes. It is able to stratify COVID-19 patients into four severity classes, with in-hospital mortality rates of 0% in group 1, 6-12.5% in group 2, 7-20% in group 3 and 60-86% in group 4 across the derivation and validation sample. The prediction model derived in this study identifies COVID-19 patients with low risk of in-hospital mortality and ICU admission. The prediction model that the study presents identifies COVID-19 patients with low risk of in-hospital mortality and admission to ICU. Moreover, it establishes an intermediate portion of patients that should be treated accurately in order to avoid an unfavourable clinical evolution. A further validation of the model is important before its implementation as a decision-making tool to guide the initial management of patients. Twit Text FOAVip Derivation and validation of the clinical prediction model for COVID-19 ????Intern Emerg Med http://www.kidney.de/pget.php?&tw=1&pmid=32930963 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32930963 #FOAvip English Wikipedia <ref>{{Cite pmid|32930963}}</ref> Derivation and validation of the clinical prediction model for COVID-19 #MMPMID32930963 Foieni F; Sala G; Mognarelli JG; Suigo G; Zampini D; Pistoia M; Ciola M; Ciampani T; Ultori C; Ghiringhelli P Intern Emerg Med 2020[Nov]; 15 (8): 1409-1414 PMID32930963show ga The epidemic phase of Coronavirus disease 2019 (COVID-19) made the Worldwide health system struggle against a severe interstitial pneumonia requiring high-intensity care settings for respiratory failure. A rationalisation of resources and a specific treatment path were necessary. The study suggests a predictive model drawing on clinical data gathered by 119 consecutive patients with laboratory-confirmed COVID-19 admitted in Busto Arsizio hospital. We derived a score that identifies the risk of clinical evolution and in-hospital mortality clustering patients into four groups. The study outcomes have been compared across the derivation and validation samples. The prediction rule is based on eight simple patient characteristics that were independently associated with study outcomes. It is able to stratify COVID-19 patients into four severity classes, with in-hospital mortality rates of 0% in group 1, 6-12.5% in group 2, 7-20% in group 3 and 60-86% in group 4 across the derivation and validation sample. The prediction model derived in this study identifies COVID-19 patients with low risk of in-hospital mortality and ICU admission. The prediction model that the study presents identifies COVID-19 patients with low risk of in-hospital mortality and admission to ICU. Moreover, it establishes an intermediate portion of patients that should be treated accurately in order to avoid an unfavourable clinical evolution. A further validation of the model is important before its implementation as a decision-making tool to guide the initial management of patients. |*Clinical Decision Rules[MESH] |Adult[MESH] |Aged[MESH] |Aged, 80 and over[MESH] |COVID-19[MESH] |Coronavirus Infections/*diagnosis/physiopathology[MESH] |Female[MESH] |Humans[MESH] |Male[MESH] |Middle Aged[MESH] |Pandemics[MESH] |Pneumonia, Viral/*diagnosis/physiopathology[MESH] |Reproducibility of Results[MESH] |Risk Assessment/methods/*standards/statistics & numerical data[MESH]Derivation and validation of the clinical prediction model for COVID-1(epmc).pdf DeepDyve Pubget Overpricing