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Depression is common among elderly patients hospitalized due to acute conditions like strokes or osteoporotic fractures. It has significant impacts on quality of life, hospitalization rates, and mortality. Although studies have explored depression and its assessment, most focus on non-geriatric or ambulatory populations. This study examined depressive symptoms in elderly patients after a stroke or fracture. We assessed all patients for depression symptoms using the validated Geriatric Depression Scale - 15 item (GDS-15) and searched for contributing factors in each condition.
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Depression is a common condition among elderly patients hospitalized due to acute events and has both short-term and long-term prognostic impacts, including reduced quality of life, recurrent hospitalizations, and even mortality. Numerous studies have examined the effects of depression and the ability to assess it, but most have been conducted in non-geriatric populations and in ambulatory patients. It remains unclear whether different acute conditions are associated with distinct risk factors for depressive symptoms and whether depressive symptoms may have varying impacts across different acute conditions. In this study, we examined depressive symptoms in two groups of elderly patients-those with stroke and those with osteoporotic fractures. These are two common acute conditions in the geriatric population, both with significant implications for patient function and the incidence of depression.
Patients were recruited from a large geriatric hospital; all patients were capable of signing consent forms. At the beginning of their hospitalization, all patients will undergo a standardized depression screening test (GDS-15), and additional data will be collected from computerized medical records, including baseline data and the Functional Independence Measure (FIM) at the beginning and end of rehabilitation. Statistical analyses, including univariate analyses and multivariate regression, will be conducted to identify variables associated with depressive symptoms. Linear regression models will be constructed for each group based on the variables significantly associated with depression to assess the risk of depression according to the identified risk factors. To evaluate the risk of depression according to the models and assess the predicted GDS value's ability to classify participants with or without depression ROC curves will be used and AUC will be calculated.
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400 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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