학술논문

Patient profiles in heart failure with reduced ejection fraction: Prevalence, characteristics, treatments and outcomes in a real-world heart failure population
Document Type
Source
European Journal of Heart Failure. 25(8):1246-1253
Subject
Heart failure
Profiles
Phenotypes
Registry
SwedeHF
Guidelines
Language
English
ISSN
1388-9842
1879-0844
Abstract
Aims The Heart Failure Association of the European Society of Cardiology has recently proposed to optimize guideline-directed medical treatments according to patient s profiles. The aim of this analysis was to investigate prevalence/characteristics/treatments/outcomes for individual profiles Methods and results Patients with heart failure (HF) with reduced ejection fraction (HFrEF) enrolled in the Swedish Heart Failure Registry (SwedeHF) between 2013 and 2021 were considered. Among 108 profiles generated by combining different strata of renal function (by estimated glomerular filtration rate [eGFR]), systolic blood pressure (sBP), heart rate, atrial fibrillation (AF) status and presence of hyperkalaemia, 93 were identified in our cohort. Event rates for a composite of cardiovascular (CV) mortality or first HF hospitalization were calculated for each profile. The nine most frequent profiles accounting for 70.5% of the population had eGFR 30- 60 or =60 ml/min/1.73m(2), sBP 90-140mmHg and no hyperkalaemia. Heart rate and AF were evenly distributed. The highest risk of CV mortality/first HF hospitalization was observed in those with concomitant eGFR 30- 60ml/min/1.73m(2) and AF. We also identified nine profiles with the highest event rates, representing only 5% of the study population, characterized by no hyperkalaemia, even distribution among the sBP strata, predominance of eGFR < 30 ml/min/1.73m(2) and AF. The three profiles with eGFR 30- 60ml/min/1.73m(2) also showed sBP < 90 mmHg Conclusions In a real-world cohort, most patients fit in a few easily identifiable profiles; the nine profiles at highest risk of mortality/morbidity accounted for only 5% of the population. Our data might contribute to identifying profile-tailored approaches to guide drug implementation and follow-up.