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10.1002/jmv.26844 http://scihub22266oqcxt.onion/10.1002/jmv.26844 33527474!8014660!33527474     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 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 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 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 298.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 298.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Med+Virol 2021 ; 93 (5): 3015-3022 Nephropedia Template TP {{tp|p=33527474|t=2021. Development and validation of clinical prediction model to estimate the probability of death in hospitalized patients with COVID-19: Insights from a nationwide database |pdf=|usr=}}{{33527474}} gab.com Text Development and validation of clinical prediction model to estimate the probability of death in hospitalized patients with COVID-19: Insights from a nationwide database JO: J Med Virol http://www.kidney.de/pget.php?&tw=1&pmid=33527474 #FOAvip In the current study, we aimed to develop and validate a model, based on our nationwide centralized coronavirus disease 2019 (COVID-19) database for predicting death. We conducted an observational study (CORONATION-TR registry). All patients hospitalized with COVID-19 in Turkey between March 11 and June 22, 2020 were included. We developed the model and validated both temporal and geographical models. Model performances were assessed by area under the curve-receiver operating characteristic (AUC-ROC or c-index), R(2) , and calibration plots. The study population comprised a total of 60,980 hospitalized COVID-19 patients. Of these patients, 7688 (13%) were transferred to intensive care unit, 4867 patients (8.0%) required mechanical ventilation, and 2682 patients (4.0%) died. Advanced age, increased levels of lactate dehydrogenase, C-reactive protein, neutrophil-lymphocyte ratio, creatinine, albumine, and D-dimer levels, and pneumonia on computed tomography, diabetes mellitus, and heart failure status at admission were found to be the strongest predictors of death at 30 days in the multivariable logistic regression model (area under the curve-receiver operating characteristic = 0.942; 95% confidence interval: 0.939-0.945; R(2) = .457). There were also favorable temporal and geographic validations. We developed and validated the prediction model to identify in-hospital deaths in all hospitalized COVID-19 patients. Our model achieved reasonable performances in both temporal and geographic validations. Twit Text FOAVip Development and validation of clinical prediction model to estimate the probability of death in hospitalized patients with COVID-19: Insights from a nationwide database ????J Med Virol http://www.kidney.de/pget.php?&tw=1&pmid=33527474 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33527474 #FOAvip English Wikipedia <ref>{{Cite pmid|33527474}}</ref> Development and validation of clinical prediction model to estimate the probability of death in hospitalized patients with COVID-19: Insights from a nationwide database #MMPMID33527474 Tanboga IH; Canpolat U; Cetin EHO; Kundi H; Celik O; Caglayan M; Ata N; Ozeke O; Cay S; Kaymaz C; Topaloglu S J Med Virol 2021[May]; 93 (5): 3015-3022 PMID33527474show ga In the current study, we aimed to develop and validate a model, based on our nationwide centralized coronavirus disease 2019 (COVID-19) database for predicting death. We conducted an observational study (CORONATION-TR registry). All patients hospitalized with COVID-19 in Turkey between March 11 and June 22, 2020 were included. We developed the model and validated both temporal and geographical models. Model performances were assessed by area under the curve-receiver operating characteristic (AUC-ROC or c-index), R(2) , and calibration plots. The study population comprised a total of 60,980 hospitalized COVID-19 patients. Of these patients, 7688 (13%) were transferred to intensive care unit, 4867 patients (8.0%) required mechanical ventilation, and 2682 patients (4.0%) died. Advanced age, increased levels of lactate dehydrogenase, C-reactive protein, neutrophil-lymphocyte ratio, creatinine, albumine, and D-dimer levels, and pneumonia on computed tomography, diabetes mellitus, and heart failure status at admission were found to be the strongest predictors of death at 30 days in the multivariable logistic regression model (area under the curve-receiver operating characteristic = 0.942; 95% confidence interval: 0.939-0.945; R(2) = .457). There were also favorable temporal and geographic validations. We developed and validated the prediction model to identify in-hospital deaths in all hospitalized COVID-19 patients. Our model achieved reasonable performances in both temporal and geographic validations. |*Models, Statistical[MESH] |Adult[MESH] |Aged[MESH] |COVID-19/diagnosis/*mortality[MESH] |Databases, Factual[MESH] |Female[MESH] |Hospitalization/*statistics & numerical data[MESH] |Humans[MESH] |Male[MESH] |Middle Aged[MESH] |Prognosis[MESH] |Reproducibility of Results[MESH] |Risk[MESH] |SARS-CoV-2/isolation & purification[MESH]Development and validation of clinical prediction model to estimate th(epmc).pdf DeepDyve Pubget Overpricing