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10.1093/ckj/sfab037 http://scihub22266oqcxt.onion/10.1093/ckj/sfab037 33777363!7929029!33777363     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 278.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 278.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 278.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Clin+Kidney+J 2021 ; 14 (3): 805-813 Nephropedia Template TP {{tp|p=33777363|t=2021. Risk prediction of COVID-19 incidence and mortality in a large multi-national hemodialysis cohort: implications for management of the pandemic in outpatient hemodialysis settings |pdf=|usr=}}{{33777363}} gab.com Text Risk prediction of COVID-19 incidence and mortality in a large multi-national hemodialysis cohort: implications for management of the pandemic in outpatient hemodialysis settings JO: Clin Kidney J http://www.kidney.de/pget.php?&tw=1&pmid=33777363 #FOAvip BACKGROUND: Experiences from the first wave of the 2019 coronavirus disease (COVID-19) pandemic can aid in the development of future preventive strategies. To date, risk prediction models for COVID-19-related incidence and outcomes in hemodialysis (HD) patients are missing. METHODS: We developed risk prediction models for COVID-19 incidence and mortality among HD patients. We studied 38 256 HD patients from a multi-national dialysis cohort between 3 March and 3 July 2020. Risk prediction models were developed and validated, based on predictors readily available in outpatient HD units. We compared mortality among patients with and without COVID-19, matched for age, sex and diabetes. RESULTS: During the observational period, 1259 patients (3.3%) acquired COVID-19. Of these, 62% were hospitalized or died. Mortality was 22% among COVID-19 patients with odds ratios 219.8 [95% confidence interval (CI) 80.6-359] to 342.7 (95% CI 60.6-13 595.1), compared to matched patients without COVID-19. Since the first wave of the pandemic affected most European countries during the study, the risk prediction model for incidence of COVID-19 was developed and validated in European patients only [N = 22 826 area under the ROC curve(AUC)(Dev) 0.64, AUC(Val) 0.69]. The model for prediction of mortality was developed in all COVID-19 patients (AUC(Dev) 0.71, AUC(Val) 0.78). Angiotensin receptor blockers were independently associated with a lower incidence of COVID-19 in European patients. CONCLUSIONS: We identified modifiable risk factors for COVID-19 incidence and outcome in HD patients. Our risk prediction tools can be readily applied in clinical practice. This can aid in the development of preventive strategies for future waves of COVID-19. Twit Text FOAVip Risk prediction of COVID-19 incidence and mortality in a large multi-national hemodialysis cohort: implications for management of the pandemic in outpatient hemodialysis settings ????Clin Kidney J http://www.kidney.de/pget.php?&tw=1&pmid=33777363 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33777363 #FOAvip English Wikipedia <ref>{{Cite pmid|33777363}}</ref> Risk prediction of COVID-19 incidence and mortality in a large multi-national hemodialysis cohort: implications for management of the pandemic in outpatient hemodialysis settings #MMPMID33777363 Haarhaus M; Santos C; Haase M; Mota Veiga P; Lucas C; Macario F Clin Kidney J 2021[Mar]; 14 (3): 805-813 PMID33777363show ga BACKGROUND: Experiences from the first wave of the 2019 coronavirus disease (COVID-19) pandemic can aid in the development of future preventive strategies. To date, risk prediction models for COVID-19-related incidence and outcomes in hemodialysis (HD) patients are missing. METHODS: We developed risk prediction models for COVID-19 incidence and mortality among HD patients. We studied 38 256 HD patients from a multi-national dialysis cohort between 3 March and 3 July 2020. Risk prediction models were developed and validated, based on predictors readily available in outpatient HD units. We compared mortality among patients with and without COVID-19, matched for age, sex and diabetes. RESULTS: During the observational period, 1259 patients (3.3%) acquired COVID-19. Of these, 62% were hospitalized or died. Mortality was 22% among COVID-19 patients with odds ratios 219.8 [95% confidence interval (CI) 80.6-359] to 342.7 (95% CI 60.6-13 595.1), compared to matched patients without COVID-19. Since the first wave of the pandemic affected most European countries during the study, the risk prediction model for incidence of COVID-19 was developed and validated in European patients only [N = 22 826 area under the ROC curve(AUC)(Dev) 0.64, AUC(Val) 0.69]. The model for prediction of mortality was developed in all COVID-19 patients (AUC(Dev) 0.71, AUC(Val) 0.78). Angiotensin receptor blockers were independently associated with a lower incidence of COVID-19 in European patients. CONCLUSIONS: We identified modifiable risk factors for COVID-19 incidence and outcome in HD patients. Our risk prediction tools can be readily applied in clinical practice. This can aid in the development of preventive strategies for future waves of COVID-19. äRisk prediction of COVID-19 incidence and mortality in a large multi-n(epmc).pdf DeepDyve Pubget Overpricing