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10.4081/monaldi.2020.1325 http://scihub22266oqcxt.onion/10.4081/monaldi.2020.1325 32447949!ä!32447949 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 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       Monaldi+Arch+Chest+Dis 2020 ; 90 (2): ä Nephropedia Template TP {{tp|p=32447949|t=2020. Extrapolation of mortality in COVID-19: Exploring the role of age, sex, co-morbidities and health-care related occupation |pdf=|usr=}}{{32447949}} gab.com Text Extrapolation of mortality in COVID-19: Exploring the role of age, sex, co-morbidities and health-care related occupation JO: Monaldi Arch Chest Dis http://www.kidney.de/pget.php?&tw=1&pmid=32447949 #FOAvip We used a publicly available data of 44,672 patients reported by China's centre for disease control to study the role of age, sex, co-morbidities and health-care related occupation on COVID-19 mortality. The data is in the form of absolute numbers and proportions. Using the percentages, retrospective synthetic data of 100 survivors and 100 deaths were generated using random number libraries so that proportions of ages, genders, co-morbidities, and occupations were constant as in the original data. Logistic regression of the four predictor factors of age, sex, co-morbidities and occupation revealed that only age and comorbidities significantly affected mortality. Sex and occupation when adjusted for other factors in the equation were not significant predictors of mortality. Age and presence of co-morbidities correlated negatively with survival with co-efficient of -1.23 and -2.33 respectively. Odds ratio (OR) for dying from COVID-19 for every 10-year increase in age was 3.4 compared to the previous band of 10 years. OR for dying of COVID-19 was 10.3 for the presence of any of the co-morbidities. Our findings could help in triaging the patients in the emergency room and emphasize the need to protect the elderly and those with comorbidities from getting exposed. Twit Text FOAVip Extrapolation of mortality in COVID-19: Exploring the role of age, sex, co-morbidities and health-care related occupation ????Monaldi Arch Chest Dis http://www.kidney.de/pget.php?&tw=1&pmid=32447949 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32447949 #FOAvip English Wikipedia <ref>{{Cite pmid|32447949}}</ref> Extrapolation of mortality in COVID-19: Exploring the role of age, sex, co-morbidities and health-care related occupation #MMPMID32447949 Asfahan S; Deokar K; Dutt N; Niwas R; Jain P; Agarwal M Monaldi Arch Chest Dis 2020[May]; 90 (2): ä PMID32447949show ga We used a publicly available data of 44,672 patients reported by China's centre for disease control to study the role of age, sex, co-morbidities and health-care related occupation on COVID-19 mortality. The data is in the form of absolute numbers and proportions. Using the percentages, retrospective synthetic data of 100 survivors and 100 deaths were generated using random number libraries so that proportions of ages, genders, co-morbidities, and occupations were constant as in the original data. Logistic regression of the four predictor factors of age, sex, co-morbidities and occupation revealed that only age and comorbidities significantly affected mortality. Sex and occupation when adjusted for other factors in the equation were not significant predictors of mortality. Age and presence of co-morbidities correlated negatively with survival with co-efficient of -1.23 and -2.33 respectively. Odds ratio (OR) for dying from COVID-19 for every 10-year increase in age was 3.4 compared to the previous band of 10 years. OR for dying of COVID-19 was 10.3 for the presence of any of the co-morbidities. Our findings could help in triaging the patients in the emergency room and emphasize the need to protect the elderly and those with comorbidities from getting exposed. |Adolescent[MESH] |Adult[MESH] |Age Factors[MESH] |Aged[MESH] |Aged, 80 and over[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Child[MESH] |Child, Preschool[MESH] |China/epidemiology[MESH] |Comorbidity[MESH] |Coronavirus Infections/*mortality[MESH] |Diabetes Mellitus/*epidemiology[MESH] |Female[MESH] |Health Personnel/statistics & numerical data[MESH] |Humans[MESH] |Hypertension/*epidemiology[MESH] |Infant[MESH] |Infant, Newborn[MESH] |Male[MESH] |Middle Aged[MESH] |Occupations/statistics & numerical data[MESH] |Odds Ratio[MESH] |Pandemics[MESH] |Pneumonia, Viral/*mortality[MESH] |SARS-CoV-2[MESH] |Sex Factors[MESH] |Survival Rate[MESH]Extrapolation of mortality in COVID-19: Exploring the role of age, sex(epmc).pdf DeepDyve Pubget Overpricing