Patterns of pharmacological treatment in patients with atrial fibrillation: an analysis from the prospective GLORIA-AF Registry Phase III

Abstract

Abstract Background Polypharmacy (i.e., treatment with ≥ 5 drugs) is common in patients with atrial fibrillation (AF) and has been associated with suboptimal management and worse outcomes. Little is known about how prescribed drug patterns affect management and prognosis in patients with AF. Methods Based on data from the prospective global GLORIA-AF Registry Phase III (recruiting patients with AF and CHA2DS2-VASc score ≥ 1), we performed a latent class analysis to identify treatment patterns based on 14 drug classes including cardiovascular (CV) and non-CV drugs. We analysed associations with oral anticoagulant (OAC) use and risk of a composite primary outcome (all-cause death and major adverse cardiovascular events (MACE)) and secondary outcomes. Results Among 21,245 patients (mean age 70.2 ± 10.3 years, 44.9% females), we identified 6 patterns: i) Low Medicated pattern (18.3%); ii) Hypertension pattern (21.1%); iii) Heart Failure pattern (20.0%); iv) CV Prevention pattern (21.0%); v) Mixed Morbidity pattern (4.5%); and vi) High Medicated pattern (15.0%). All groups had higher odds of OAC use vs the Low Medicated pattern, with highest prevalences in the Heart Failure pattern (OR [95%CI]: 2.17 [1.90–2.48]) and the High Medicated pattern (OR [95%CI]: 2.08 [1.77–2.44]). Over 3-year follow-up, Heart Failure, Mixed Morbidity and High Medicated patterns were associated with higher risk of the primary composite outcome (aHR [95%CI]: 1.32 [1.14–1.53]; 1.45 [1.17–1.80] and 1.35 [1.14–1.60], respectively). Similar results were observed for all-cause mortality. Conclusions In patients with AF, different treatment patterns can be identified. Each pattern was associated with unique OAC use and long-term clinical outcomes.

Keywords

• Atrial Fibrillation
• Comorbidities
• Multimorbidity
• Clinical Complexity
• Latent Class Analysis