Polypharmacy and Optimization of Guideline-Directed Medical Therapy in Heart Failure Journal Articles uri icon

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abstract

  • BACKGROUND: Polypharmacy is common among patients with heart failure with reduced ejection fraction (HFrEF). However, its impact on the use of optimal guideline-directed medical therapy (GDMT) is not well established. OBJECTIVES: This study sought to evaluate the association between polypharmacy and odds of receiving optimal GDMT over time among patients with HFrEF. METHODS: The authors conducted a post hoc analysis of the GUIDE-IT (Guiding Evidence-Based Therapy Using Biomarker Intensified Treatment) trial. Polypharmacy was defined as receiving ≥5 medications (excluding HFrEF GDMT) at baseline. The outcome of interest was optimal triple therapy GDMT (concurrent administration of a renin-angiotensin-aldosterone blocker and beta-blocker at 50% of the target dose and a mineralocorticoid receptor antagonist at any dose) achieved over the 12-month follow-up. Multivariable adjusted mixed-effect logistic regression models with multiplicative interaction terms (time × polypharmacy) were constructed to evaluate how polypharmacy at baseline modified the odds of achieving optimal GDMT on follow-up. RESULTS: The study included 891 participants with HFrEF. The median number of non-GDMT medications at baseline was 4 (IQR: 3-6), with 414 (46.5%) prescribed ≥5 and identified as being on polypharmacy. The proportion of participants who achieved optimal GDMT at the end of the 12-month follow-up was lower with vs without polypharmacy at baseline (15% vs 19%, respectively). In adjusted mixed models, the odds of achieving optimal GDMT over time were modified by baseline polypharmacy status (P for interaction < 0.001). Patients without polypharmacy at baseline had increased odds of achieving GDMT (OR: 1.16 [95% CI: 1.12-1.21] per 1-month increase; P < 0.001) but not patients with polypharmacy (OR: 1.01 [95% CI: 0.96-1.06)] per 1-month increase). CONCLUSIONS: Patients with HFrEF who are on non-GDMT polypharmacy have lower odds of achieving optimal GDMT on follow-up.

authors

  • Khan, Muhammad Shahzeb
  • Singh, Sumitabh
  • Segar, Matthew W
  • Usman, Muhammad Shariq
  • Keshvani, Neil
  • Ambrosy, Andrew P
  • Fiuzat, Mona
  • Van Spall, Harriette
  • Fonarow, Gregg C
  • Zannad, Faiez
  • Felker, G Michael
  • Januzzi, James L
  • O’Connor, Christopher
  • Butler, Javed
  • Pandey, Ambarish

publication date

  • November 2023