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10.1017/dmp.2021.8 http://scihub22266oqcxt.onion/10.1017/dmp.2021.8 33413721!8007955!33413721     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Disaster+Med+Public+Health+Prep 2022 ; 16 (4): 1398-1406 Nephropedia Template TP {{tp|p=33413721|t=2022. Development of a Predictive Model for Mortality in Hospitalized Patients With COVID-19 |pdf=|usr=}}{{33413721}} gab.com Text Development of a Predictive Model for Mortality in Hospitalized Patients With COVID-19 JO: Disaster Med Public Health Prep http://www.kidney.de/pget.php?&tw=1&pmid=33413721 #FOAvip INTRODUCTION: Early identification of patients with novel corona virus disease 2019 (COVID-19) who may be at high mortality risk is of great importance. METHODS: In this retrospective study, we included all patients with COVID-19 at Huanggang Central Hospital from January 23 to March 5, 2020. Data on clinical characteristics and outcomes were compared between survivors and nonsurvivors. Univariable and multivariable logistic regression were used to explore risk factors associated with in-hospital death. A nomogram was established based on the risk factors selected by multivariable analysis. RESULTS: A total of 150 patients were enrolled, including 31 nonsurvivors and 119 survivors. The multivariable logistic analysis indicated that increasing the odds of in-hospital death associated with higher Sequential Organ Failure Assessment score (odds ratio [OR], 3.077; 95% confidence interval [CI]: 1.848-5.122; P < 0.001), diabetes (OR, 10.474; 95% CI: 1.554-70.617; P = 0.016), and lactate dehydrogenase greater than 245 U/L (OR, 13.169; 95% CI: 2.934-59.105; P = 0.001) on admission. A nomogram was established based on the results of the multivariable analysis. The AUC of the nomogram was 0.970 (95% CI: 0.947-0.992), showing good accuracy in predicting the risk of in-hospital death. CONCLUSIONS: This finding would facilitate the early identification of patients with COVID-19 who have a high-risk for fatal outcome. Twit Text FOAVip Development of a Predictive Model for Mortality in Hospitalized Patients With COVID-19 ????Disaster Med Public Health Prep http://www.kidney.de/pget.php?&tw=1&pmid=33413721 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33413721 #FOAvip English Wikipedia <ref>{{Cite pmid|33413721}}</ref> Development of a Predictive Model for Mortality in Hospitalized Patients With COVID-19 #MMPMID33413721 Niu Y; Zhan Z; Li J; Shui W; Wang C; Xing Y; Zhang C Disaster Med Public Health Prep 2022[Aug]; 16 (4): 1398-1406 PMID33413721show ga INTRODUCTION: Early identification of patients with novel corona virus disease 2019 (COVID-19) who may be at high mortality risk is of great importance. METHODS: In this retrospective study, we included all patients with COVID-19 at Huanggang Central Hospital from January 23 to March 5, 2020. Data on clinical characteristics and outcomes were compared between survivors and nonsurvivors. Univariable and multivariable logistic regression were used to explore risk factors associated with in-hospital death. A nomogram was established based on the risk factors selected by multivariable analysis. RESULTS: A total of 150 patients were enrolled, including 31 nonsurvivors and 119 survivors. The multivariable logistic analysis indicated that increasing the odds of in-hospital death associated with higher Sequential Organ Failure Assessment score (odds ratio [OR], 3.077; 95% confidence interval [CI]: 1.848-5.122; P < 0.001), diabetes (OR, 10.474; 95% CI: 1.554-70.617; P = 0.016), and lactate dehydrogenase greater than 245 U/L (OR, 13.169; 95% CI: 2.934-59.105; P = 0.001) on admission. A nomogram was established based on the results of the multivariable analysis. The AUC of the nomogram was 0.970 (95% CI: 0.947-0.992), showing good accuracy in predicting the risk of in-hospital death. CONCLUSIONS: This finding would facilitate the early identification of patients with COVID-19 who have a high-risk for fatal outcome. |*COVID-19[MESH] |Hospital Mortality[MESH] |Humans[MESH] |Prognosis[MESH] |Retrospective Studies[MESH]Development of a Predictive Model for Mortality in Hospitalized Patien(epmc).pdf DeepDyve Pubget Overpricing