Research Information System
European Journal of Clinical Pharmacology, vol.82, no.2, 2026 (SCI-Expanded, Scopus)
Background: Heart failure (HF) patients with concomitant coronary artery disease (CAD) and type 2 diabetes mellitus (DM) represent a particularly high-risk population with increased morbidity and mortality. Acute coronary syndrome (ACS) often serves as a critical event that can trigger optimization of guideline-directed medical therapy (GDMT). However, the impact of ACS on long-term adherence patterns and outcomes in this population remains unclear. Methods: We retrospectively studied 431 patients with HF (LVEF ≤ 40%), CAD, and DM presenting with ACS between 2019 and 2022. Adherence to nine evidence-based therapies was scored (0–9) and classified as poor (0–3), intermediate (4-6), or good (7-9). Adherence was assessed before ACS and over 36 months of follow-up. Primary outcomes were rehospitalization and all-cause mortality, analyzed using Cox regression and Kaplan–Meier methods. Results: Mean age was 62.1 ± 10.2 years, and 64.7% were male. Before ACS, 45.9% had poor adherence and only 16.0% had good adherence. After ACS, poor adherence dropped to 7.9%, while good adherence rose to 62.2% (p < 0.001). Statin use increased from 22.3% to 82.4%, ACEi/ARB/ARNI from 58.2% to 89.3%, beta-blockers from 44.8% to 86.8%, and MRAs from 23.4% to 67.3%. Gender-specific analyses showed parallel gains: poor adherence declined from 44.8% to 6.5% in men and from 40.1% to 5.3% in women, with good adherence exceeding 67% in both groups. Patients with good adherence had significantly lower risks of rehospitalization (HR 0.52) and mortality (HR 0.46). Independent adverse outcome predictors were low hemoglobin, high HbA1c, impaired renal function, and reduced LVEF. Conclusion: ACS serves as a catalyst for improved GDMT adherence in HF patients with CAD and DM. Higher adherence is strongly associated with reduced rehospitalization and mortality, underscoring the need for sustained adherence strategies and multidisciplinary care models to optimize long-term outcomes.