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Multi-Symptom Profile Predicts Increased Risk of Poor Outcomes Following Initial Placement of Implantable Cardioverter Defibrillator.
Journal of Pain and Symptom Management 2019 November 8
CONTEXT: Patients with implantable cardioverter defibrillators (ICD) are at risk for multiple physical and psychological symptoms. Identification of specific symptom profiles associated with poor outcomes may elucidate novel strategies to enhance symptom management.
OBJECTIVES: The objectives were to determine common symptoms following initial ICD implant, identify classes of individuals with similar symptom profiles, describe patient characteristics associated with different symptom profiles, and determine if symptom profiles at hospital discharge predicted outcomes 3 and 12 months post-implant.
METHODS: This was a secondary data analysis of a randomized controlled trial that compared Patient+Partner versus Patient-Only interventions designed to help patients manage symptoms, prepare for ICD shocks, and resume daily activities. Symptoms were measured with the Patient Concerns Assessment. Latent class regression analysis was used to identify symptom classes at baseline, 3- and 12-month follow-up. Associations between patient characteristics, class membership, and outcomes were examined using chi-square, analysis of variance, and Poisson regression.
RESULTS: The study included 301 patients (74% male, mean age 64±11.9 years). Three classes were identified: Multi-Symptom (N=119, 40%), Tired-Rundown (N=130, 43%), and Mostly Asymptomatic (N=52, 17%). Patients in the Multi-Symptom class were younger (59.9 years, p < 0.001), and reported more anxiety (p < 0.001) and depression (p < 0.01) than the other classes. Membership in the Multi-Symptom class predicted lower quality of life and nearly double the rate of hospitalizations after 12 months (p = 0.02, IRR 1.9).
CONCLUSION: Evaluation of symptom profiles after ICD implantation offers a promising strategy for identifying patients at risk for poor health outcomes.
OBJECTIVES: The objectives were to determine common symptoms following initial ICD implant, identify classes of individuals with similar symptom profiles, describe patient characteristics associated with different symptom profiles, and determine if symptom profiles at hospital discharge predicted outcomes 3 and 12 months post-implant.
METHODS: This was a secondary data analysis of a randomized controlled trial that compared Patient+Partner versus Patient-Only interventions designed to help patients manage symptoms, prepare for ICD shocks, and resume daily activities. Symptoms were measured with the Patient Concerns Assessment. Latent class regression analysis was used to identify symptom classes at baseline, 3- and 12-month follow-up. Associations between patient characteristics, class membership, and outcomes were examined using chi-square, analysis of variance, and Poisson regression.
RESULTS: The study included 301 patients (74% male, mean age 64±11.9 years). Three classes were identified: Multi-Symptom (N=119, 40%), Tired-Rundown (N=130, 43%), and Mostly Asymptomatic (N=52, 17%). Patients in the Multi-Symptom class were younger (59.9 years, p < 0.001), and reported more anxiety (p < 0.001) and depression (p < 0.01) than the other classes. Membership in the Multi-Symptom class predicted lower quality of life and nearly double the rate of hospitalizations after 12 months (p = 0.02, IRR 1.9).
CONCLUSION: Evaluation of symptom profiles after ICD implantation offers a promising strategy for identifying patients at risk for poor health outcomes.
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