Biomedical Research

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Research Article - Biomedical Research (2017) Volume 28, Issue 16

Impact of the disease management model of "treatment-education-follow-up" on anticoagulant therapy in patients with stroke and atrial fibrillation

Long-term anticoagulant therapy is the most effective measure to prevent ischemic stroke in patients with Atrial Fibrillation (AF). However, the current anticoagulant therapy in Chinese patients with AF is unsatisfactory compared to those in developed countries. Disease management may help improve the treatment rate, reduce adverse events, and improve the compliance to warfarin anticoagulant therapy. The aim of this study was to compare and observe the impact of the disease management model of “Treatment-Education-Follow-up” (TEF) on anticoagulant therapy in patients with Stroke with AF (SAF). The patients and their families in group TEF were educated on anticoagulant therapy by providing them S-AF prevention and anticoagulant therapy handbooks and performing regular post-discharge telephone follow-up and outpatient observation. Conversely, the patients in the control group (group N) only received simple education; no other education and intervention from the doctors were provided during hospitalization. The mean follow-up duration was 1.5 y. The clinical data, 8-item Morisky Medication Adherence Scale scores, and anticoagulant knowledge questionnaire scores were compared between the two groups. The persistence rate of long-term anticoagulant therapy (84.5% vs. 56.0%, P<0.05), international normalized ratio compliance rate (55.2% vs. 28.0%, P<0.05), and recurrence rate of thrombotic events (4.0% vs. 16.0%, P<0.05) in group TEF were statistically significant compared with those of group N. The medication compliance and anticoagulant knowledge in group TEF significantly improved. Clinical anticoagulation service-based TEF can significantly improve the efficacy and safety of and compliance to warfarin anticoagulant therapy.

Author(s): Tieyu Tang, Xinjiang Zhang, Lihong Tao, Anxiu Sun, Shenggang Qiu, Fushan Zhang, Bing Xie, Xiaodong Jiao, Xuhong Liu, Lan Tan

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