A Computable Algorithm for Medication Optimization in Heart Failure With Reduced Ejection Fraction

被引:2
作者
Dorsch, Michael P. [1 ,2 ]
Sifuentes, Aaron [3 ]
Cordwin, David J. [1 ]
Kuo, Rachel [1 ]
Rowell, Brigid E. [1 ]
Arzac, Juan J. [1 ]
DeBacker, Ken [1 ]
Guidi, Jessica L. [2 ,3 ]
Hummel, Scott L. [2 ,3 ,4 ]
Koelling, Todd M. [2 ,3 ]
机构
[1] Univ Michigan, Coll Pharm, Dept Clin Pharm, Ann Arbor, MI USA
[2] Univ Michigan, Frankel Cardiovasc Ctr, Ann Arbor, MI USA
[3] Univ Michigan, Med Sch, Dept Internal Med, Ann Arbor, MI USA
[4] Ann Arbor Vet Affairs Hlth Syst, Ann Arbor, MI USA
来源
JACC-ADVANCES | 2023年 / 2卷 / 03期
基金
美国国家卫生研究院;
关键词
computable knowledge; digital health; health technology; heart failure; quality and outcomes; statements and guidelines; SYSTOLIC DYSFUNCTION; RANDOMIZED-TRIAL; MORTALITY; MORBIDITY; SURVIVAL; THERAPIES; ENALAPRIL; ADHERENCE;
D O I
10.1016/j.jacadv.2023.100289
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
BACKGROUND Guideline-directed medical therapy (GDMT) optimization can improve outcomes in heart failure with reduced ejection fraction. OBJECTIVES The objective of this study was to determine if a novel computable algorithm appropriately recommended GDMT. METHODS Clinical trial data from the GUIDE-IT (Guiding Evidence-Based Therapy Using Biomarker Intensified Treatment in Heart Failure) and HF-ACTION (Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training) trials were evaluated with a computable medication optimization algorithm that outputs GDMT recommendations and a medication optimization score (MOS). Algorithm-based recommendations were compared to medication changes. A Cox proportional-hazards model was used to estimate the associations between MOS and the composite primary end point for both trials. RESULTS The algorithm recommended initiation of angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, beta-blockers, and mineralocorticoid receptor antagonists in 52.8%, 34.9%, and 68.1% of GUIDE-IT visits, respectively, when not prescribed the drug. Initiation only occurred in 20.8%, 56.9%, and 15.8% of subsequent visits. The algorithm also identified dose titration in 48.8% of visits for angiotensin-converting enzyme inhibitor/angiotensin receptor blockers and 39.4% of visits for beta-blockers. Those increases only occurred in 24.3% and 36.8% of subsequent visits. A higher baseline MOS was associated with a lower risk of cardiovascular death or heart failure hospitalization (HR: 0.41; 95% CI: 0.21-0.80; P = 0.009) in GUIDE-IT and all-cause death and hospitalization (HR: 0.61; 95% CI: 0.44-0.84; P = 0.003) in HF-ACTION. CONCLUSIONS The algorithm accurately identified patients for GDMT optimization. Even in a clinical trial with robust protocols, GDMT could have been further optimized in a meaningful number of visits. The algorithm-generated MOS was associated with a lower risk of clinical outcomes. Implementation into clinical care may identify and address suboptimal GDMT in patients with heart failure with reduced ejection fraction.
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页数:10
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