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Predictors of patient adherence to COPD self-management exacerbation action plans.

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OBJECTIVE Identifying patient characteristics predicting categories of patient adherence to Chronic Obstructive Pulmonary Disease (COPD) exacerbation action plans. METHODS Data were obtained from self-treatment intervention groups of two COPD self-management… Click to show full abstract

OBJECTIVE Identifying patient characteristics predicting categories of patient adherence to Chronic Obstructive Pulmonary Disease (COPD) exacerbation action plans. METHODS Data were obtained from self-treatment intervention groups of two COPD self-management trials. Patients with ≥1 exacerbation and/or ≥1 self-initiated prednisolone course during one-year follow-up were included. Optimal treatment was defined as 'self-initiating prednisolone treatment ≤2 days from the onset of a COPD exacerbation'. Predictors of adherence categories were identified by multinomial logistic regression analysis using patient characteristics. RESULTS 145 COPD patients were included and allocated to four adherence categories: 'optimal treatment' (26.2 %), 'sub optimal treatment' (11.7 %), 'significant delay or no treatment' (31.7 %), or 'treatment outside the actual exacerbation period' (30.3 %). One unit increase in baseline dyspnoea score (mMRC scale 0-4) increased the risk of 'significant delay or no treatment' (OR 1.64 (95 % CI 1.07-2.50)). Cardiac comorbidity showed a borderline significant increased risk of 'treatment outside the actual exacerbation period' (OR 2.40 (95 % CI 0.98-5.85)). CONCLUSION More severe dyspnoea and cardiac comorbidity may lower adherence to COPD exacerbation action plans. PRACTICE IMPLICATIONS Tailored self-management support with more focus on dyspnoea and cardiac disease symptoms may help patients to better act upon increased exacerbation symptoms and improve adherence to COPD exacerbation action plans.

Keywords: treatment; exacerbation action; action plans; exacerbation; adherence

Journal Title: Patient education and counseling
Year Published: 2020

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