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Course of depression and mortality among older primary care patients
Hillary R Bogner1, Knashawn H Morales, Charles F Reynolds
1Department of Family Medicine and Community Health, University of Pennsylvania, Philadelphia, PA 19104, USA. hillary.bogner@uphs.upenn.edu
Context:
: Depression is a treatable illness that disproportionately places older adults at increased risk for mortality.
Objective:
: We sought to examine whether there are patterns of course of depression severity among older primary care patients that are associated with increased risk for mortality.
Design And Setting:
: Our study was a secondary analysis of data from a practice-based randomized controlled trial within 20 primary care practices located in greater New York City, Philadelphia, and Pittsburgh.
Participants:
: The study sample consisted of 599 adults aged 60 years and older recruited from primary care settings. Participants were identified though a two-stage, age-stratified (60-74 years; older than 75 years) depression screening of randomly sampled patients. Severity of depression was assessed using the 24-item Hamilton Depression Rating Scale (HDRS).
Measurements:
: Longitudinal analysis via growth curve mixture modeling was carried out to classify patterns of course of depression severity across 12 months. Vital status at 5 years was ascertained via the National Death Index Plus.
Results:
: Three patterns of change in course of depression severity over 12 months were identified: 1) persistent depressive symptoms, 2) high but declining depressive symptoms, 3) low and declining depressive symptoms. After a median follow-up of 52.0 months, 114 patients had died. Patients with persistent depressive symptoms were more likely to have died compared with patients with a course of high but declining depressive symptoms (adjusted hazard ratio 2.32, 95% confidence interval [1.15-4.69]).
Conclusions:
: Persistent depressive symptoms signaled increased risk of dying in older primary care patients, even after adjustment for potentially influential characteristics such as age, smoking status, and medical comorbidity.
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