Longjian Liu1, Dennis H Sullivan. 1. Geriatric Research, Education and Clinical Center, Central Arkansas Veterans Healthcare System, Little Rock, Arkansas 72205, USA.
Abstract
BACKGROUND: Little is known about the impact of social demographic factors on post-discharge mortality among the hospitalized elderly. METHODS: A one-year prospective study was conducted in a random sample of 646 male patients aged 65 or older who were discharged from a university affiliated Veterans Administration Hospital at Little Rock, AR, USA. Within 48 hours of admission, each subject completed a standardized diagnostic evaluation. Mortality was recorded for all causes. Associations between patient characteristics at hospital discharge and mortality were identified utilizing univariable and multivariable (Cox proportional hazard regression) statistical techniques. RESULTS: The mean (SD) age was 73(+/- 6) years. Within one year of hospital discharge, 83 patients (13%) died. Multiple social demographic factors were significantly associated with mortality in univariable analysis. After controlling for age, Katz index of ADL score, Charlson co-morbidity index and length of hospitalization, risk of one-year post-discharge mortality remained significantly associated with marital status, race, education, and occupational class. When all of the social demographic factors were included in a stepwise procedure, marital status, education and occupational class were selected as the strongest predictors of mortality. The adjusted hazard ratios (95% confidence interval) of mortality associated with non-married status, education < 6 years, and history of having a blue-collar occupation were 2.01 (1.29-3.15), 1.86 (1.05-3.32), and 2.16 (1.03-4.54) respectively. CONCLUSION: The results suggest that social demographic factors are independent determinants of mortality among elderly patients. These factors should be used as important indices in identifying patients at higher risk of death in clinical assessments and in prevention programs for elderly patients after hospital discharge.
BACKGROUND: Little is known about the impact of social demographic factors on post-discharge mortality among the hospitalized elderly. METHODS: A one-year prospective study was conducted in a random sample of 646 male patients aged 65 or older who were discharged from a university affiliated Veterans Administration Hospital at Little Rock, AR, USA. Within 48 hours of admission, each subject completed a standardized diagnostic evaluation. Mortality was recorded for all causes. Associations between patient characteristics at hospital discharge and mortality were identified utilizing univariable and multivariable (Cox proportional hazard regression) statistical techniques. RESULTS: The mean (SD) age was 73(+/- 6) years. Within one year of hospital discharge, 83 patients (13%) died. Multiple social demographic factors were significantly associated with mortality in univariable analysis. After controlling for age, Katz index of ADL score, Charlson co-morbidity index and length of hospitalization, risk of one-year post-discharge mortality remained significantly associated with marital status, race, education, and occupational class. When all of the social demographic factors were included in a stepwise procedure, marital status, education and occupational class were selected as the strongest predictors of mortality. The adjusted hazard ratios (95% confidence interval) of mortality associated with non-married status, education < 6 years, and history of having a blue-collar occupation were 2.01 (1.29-3.15), 1.86 (1.05-3.32), and 2.16 (1.03-4.54) respectively. CONCLUSION: The results suggest that social demographic factors are independent determinants of mortality among elderly patients. These factors should be used as important indices in identifying patients at higher risk of death in clinical assessments and in prevention programs for elderly patients after hospital discharge.
Authors: Sabina Dang; Justin R Shinn; Benjamin R Campbell; Gaelyn Garrett; Christopher Wootten; Alexander Gelbard Journal: Laryngoscope Date: 2019-07-29 Impact factor: 3.325