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10.1002/hec.4208 http://scihub22266oqcxt.onion/10.1002/hec.4208 33368853!ä!33368853 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 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       Health+Econ 2021 ; 30 (3): 699-707 Nephropedia Template TP {{tp|p=33368853|t=2021. Estimating (quality-adjusted) life-year losses associated with deaths: With application to COVID-19 |pdf=|usr=}}{{33368853}} gab.com Text Estimating (quality-adjusted) life-year losses associated with deaths: With application to COVID-19 JO: Health Econ http://www.kidney.de/pget.php?&tw=1&pmid=33368853 #FOAvip Many epidemiological models of the COVID-19 pandemic have focused on preventing deaths. Questions have been raised as to the frailty of those succumbing to the COVID-19 infection. In this paper we employ standard life table methods to illustrate how the potential quality-adjusted life-year (QALY) losses associated with COVID-19 fatalities could be estimated, while adjusting for comorbidities in terms of impact on both mortality and quality of life. Contrary to some suggestions in the media, we find that even relatively elderly patients with high levels of comorbidity can still lose substantial life years and QALYs. The simplicity of the method facilitates straightforward international comparisons as the pandemic evolves. In particular, we compare five different countries and show that differences in the average QALY losses for each COVID-19 fatality is driven mainly by differing age distributions for those dying of the disease. Twit Text FOAVip Estimating (quality-adjusted) life-year losses associated with deaths: With application to COVID-19 ????Health Econ http://www.kidney.de/pget.php?&tw=1&pmid=33368853 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33368853 #FOAvip English Wikipedia <ref>{{Cite pmid|33368853}}</ref> Estimating (quality-adjusted) life-year losses associated with deaths: With application to COVID-19 #MMPMID33368853 Briggs AH; Goldstein DA; Kirwin E; Meacock R; Pandya A; Vanness DJ; Wisloff T Health Econ 2021[Mar]; 30 (3): 699-707 PMID33368853show ga Many epidemiological models of the COVID-19 pandemic have focused on preventing deaths. Questions have been raised as to the frailty of those succumbing to the COVID-19 infection. In this paper we employ standard life table methods to illustrate how the potential quality-adjusted life-year (QALY) losses associated with COVID-19 fatalities could be estimated, while adjusting for comorbidities in terms of impact on both mortality and quality of life. Contrary to some suggestions in the media, we find that even relatively elderly patients with high levels of comorbidity can still lose substantial life years and QALYs. The simplicity of the method facilitates straightforward international comparisons as the pandemic evolves. In particular, we compare five different countries and show that differences in the average QALY losses for each COVID-19 fatality is driven mainly by differing age distributions for those dying of the disease. |*Quality-Adjusted Life Years[MESH] |Adolescent[MESH] |Adult[MESH] |Age Distribution[MESH] |Aged[MESH] |Aged, 80 and over[MESH] |COVID-19/*mortality[MESH] |Child[MESH] |Child, Preschool[MESH] |Comorbidity[MESH] |Humans[MESH] |Infant[MESH] |Life Expectancy/*trends[MESH] |Middle Aged[MESH] |Pandemics[MESH] |Quality of Life[MESH] |SARS-CoV-2[MESH] |Time Factors[MESH] |United Kingdom/epidemiology[MESH]Estimating (quality-adjusted) life-year losses associated with deaths:(epmc).pdf DeepDyve Pubget Overpricing