Predicting Long‐Term Mortality of Older Adults After Acute Care Discharge: Results From the Geriatric Emergency Department Elderly populatioN Cohort Study

To the Editor: Elderly adults are the fastest-growing group of individuals admitted to the hospital, generally through the emergency department (ED).1 Older adults are at greater risk than younger individuals of in-hospital adverse outcomes, leading to a greater prevalence of in-hospital mortality.2 Previous studies have attempted to develop screening tools, such as the 6-item brief geriatric assessment (BGA), to identify older inpatients at risk of in-hospital adverse outcomes because these tools might be helpful in targeting resources and interventions for vulnerable older inpatients.2, 3 In-hospital adverse outcomes are strongly related to postdischarge mortality.4 Determining the long-term risk of postdischarge mortality has not been fully examined. Long hospital stays, which might be considered as a surrogate measure of in-hospital adverse outcomes, have higher short- and medium-term risk of death after hospital discharge.4 Because the 6-item BGA can be used to predict length of hospital stay, it was hypothesized that it could also predict long-term postdischarge mortality. The current study was designed to examine whether the 6-item BGA could predict the risk of long-term mortality after acute care discharge of older adults. Three hundred forty-three older adults (mean age 84.7 ± 5.4, 62.0% female) were prospectively included in the geriatric Emergency Department Elderly populatioN (EDEN) study from February to April 2011. The inclusion criteria were an unplanned admission to the ED by primary care physicians followed by discharge to an acute care unit of Angers University Hospital, France; aged 75 and older; and willingness to participate. The 6-item BGA was performed upon ED admission. Information was recorded on age (≥85, < 85), sex, taking more than four drugs per day, use of formal or informal home-help services (yes, no), history of fall in previous 6 months (yes, no), ability to give month or year (yes, no), residence (home, institution), and reason for admission to ED. Information on mortality was collected through a systematic telephone call and by consulting the administrative registry of Angers University Hospital 36 months after hospital discharge. The Angers ethics committee approved the project. Cox regression models were used to examine the association between postdischarge mortality and a priori combinations of BGA items identifying three risk-levels (low, intermediate, high). Two types of Cox regression models were distinguished: univariate model and multiple regression models, using low-risk level as the reference. A priori combinations of BGA items was developed for risk of long hospital stay,5 with history of falls and cognitive decline indicating high risk; aged 85 and older, male sex, taking more than four drugs per day, no use of home services, and cognitive decline, or history of falls indicating intermediate risk; and three or fewer of aged 85 and older, male sex, taking fewer than five drugs per day, and no use of home services indicating low risk. P < .05 was considered statistically significant. All analyses were performed using SPSS version 19.0 (SPSS, Inc., Chicago, IL). Cox regression models showed that individuals with low-risk BGA combinations had a low risk of dying after discharge (hazard ratio (HR) = 0.44, P < .001; HR adjusted for reason for ED admission and residence (aHR) = 0.47, P = .001) (Table 1). Individuals with intermediate-risk BGA combinations had a high risk of dying after discharge (HR = 1.66, P = .004; aHR = 1.62, P = .006). High-risk BGA combinations did not predict postdischarge mortality. Using the low-risk combination as the reference group, intermediate- (HR = 2.24, P < .001; aHR = 2.14, P < .001) and high-risk (HR = 2.26, P = .002; aHR = 2.03, P = .01) BGA combinations successfully predicted higher risk of postdischarge mortality. A priori BGA combinations successfully predicted risk of long-term postdischarge mortality. High- and intermediate-risk a priori combinations mainly included items related to cognitive and mobility disorders, which have been previously associated with mortality in older hospitalized adults.6 Most previous studies have analyzed short-term in-hospital mortality or long-term postdischarge mortality for specific medical conditions such as hip fracture.7, 8 The current results, combined with the fact that the 6-item BGA may also predict length of hospital stay,4 suggest that it could be used to identify frail older hospitalized adults early. Further research is needed to corroborate this finding. We are grateful to the participants for their cooperation. Conflict of Interest: Prof. Beauchet has served as an unpaid consultant to Ipsen Pharma and serves as an associate editor for Gériatrie, Psychologie et Neuropsychiatrie du Vieillissement. He has no relevant financial interest in this manuscript. Authors Contribution: Launay has full access to the data in the study. Launay, Beauchet, and Scholastique: study concept and design. Joly, Scholastique: data acquisition. Kabeshova, Launay: data analysis and interpretation. Scholastique, Launay, Beauchet, Joly: drafting of the manuscript. Beauchet, Launay: critical revision of manuscript for important intellectual content. Kabeshova: statistical expertise. Launay: administrative, technical, material support. Beauchet and Launay: study supervision. Sponsor's Role: Not applicable.

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