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Different Pathophysiology and Outcomes of Heart Failure With Preserved Ejection Fraction Stratified by K-Means Clustering.

ABSTRACT: Background: Stratified medicine may enable the development of effective treatments for particular groups of patients with heart failure with preserved ejection fraction (HFpEF); however, the heterogeneity of this syndrome makes it difficult to group patients together by common disease features. The aim of the present study was to find new subgroups of HFpEF using machine learning. Methods: K-means clustering was used to stratify patients with HFpEF. We retrospectively enrolled 350 outpatients with HFpEF. Their clinical characteristics, blood sample test results and hemodynamic parameters assessed by echocardiography, electrocardiography and jugular venous pulse, and clinical outcomes were applied to k-means clustering. The optimal k was detected using Hartigan's rule. Results: HFpEF was stratified into four groups. The characteristic feature in group 1 was left ventricular relaxation abnormality. Compared with group 1, patients in groups 2, 3, and 4 had a high mean mitral E/e' ratio. The estimated glomerular filtration rate was lower in group 2 than in group 3 (median 51 ml/min/1.73 m² vs. 63 ml/min/1.73 m² p < 0.05). The prevalence of less-distensible right ventricle and atrial fibrillation was higher, and the deceleration time of mitral inflow was shorter in group 3 than in group 2 (93 vs. 22% p < 0.05, 95 vs. 1% p < 0.05, and median 167 vs. 223 ms p < 0.05, respectively). Group 4 was characterized by older age (median 85 years) and had a high systolic pulmonary arterial pressure (median 37 mmHg), less-distensible right ventricle (89%) and renal dysfunction (median 54 ml/min/1.73 m²). Compared with group 1, group 4 exhibited the highest risk of the cardiac events (hazard ratio [HR]: 19; 95% confidence interval [CI] 8.9-41); group 2 and 3 demonstrated similar rates of cardiac events (group 2 HR: 5.1; 95% CI 2.2-12; group 3 HR: 3.7; 95%CI, 1.3-10). The event-free rates were the lowest in group 4 (p for trend < 0.001). Conclusions: K-means clustering divided HFpEF into 4 groups. Older patients with HFpEF may suffer from complication of RV afterload mismatch and renal dysfunction. Our study may be useful for stratified medicine for HFpEF.

SUBMITTER: Harada D

PROVIDER: S-EPMC7734143 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Different Pathophysiology and Outcomes of Heart Failure With Preserved Ejection Fraction Stratified by K-Means Clustering.

Harada Daisuke D Asanoi Hidetsugu H Noto Takahisa T Takagawa Junya J

Frontiers in cardiovascular medicine 20201130

<b>Background:</b> Stratified medicine may enable the development of effective treatments for particular groups of patients with heart failure with preserved ejection fraction (HFpEF); however, the heterogeneity of this syndrome makes it difficult to group patients together by common disease features. The aim of the present study was to find new subgroups of HFpEF using machine learning. <b>Methods:</b> K-means clustering was used to stratify patients with HFpEF. We retrospectively enrolled 350 ...[more]

PMID: 33330670

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Project description:Heart Failure (HF) is the most common cause of hospitalization in the Western societies. HF is a heterogeneous and complex syndrome that may result from any dysfunction of systolic or diastolic capacity. Abnormal diastolic left ventricular function with impaired relaxation and increased diastolic stiffness is characteristic of heart failure with preserved ejection fraction (HFpEF). HFpEF accounts for more than 50% of all cases of HF. The prevalence increases with age: from around 1% for those aged <55 years to >10% in those aged 70 years or over. Nearly 50% of HF patients have HFrEF and the other 50% have HFpEF/HFmrEF, mainly based on studies in hospitalized patients. The ESC Long-Term Registry, in the outpatient setting, reports that 60% have HFrEF, 24% have HFmrEF, and 16% have HFpEF. To some extent, more than 50% of HF patients are female. HFpEF is closely associated with co-morbidities, age, and gender. Epidemiological evidence suggests that HFpEF is highly represented in older obese women and proposed as 'obese female HFpEF phenotype'. While HFrEF phenotype is more a male phenotype. In addition, metabolic abnormalities and hemodynamic perturbations in obese HFpEF patients appear to have a greater impact in women then in men (Sorimachi et al., European J of Heart Fail, 2022, 22). To date, numerous clinical trials of HFpEF treatments have produced disappointing results. This outcome suggests that a "one size fits all" approach to HFpEF may be inappropriate and supports the use of tailored, personalized therapeutic strategies with specific treatments for distinct HFpEF phenotypes. The most important mediators of diastolic stiffness are the cardiomyocytes, endothelial cells, and extracellular matrix (ECM). The complex physiological signal transduction networks that respond to the dual challenges of inflammatory and oxidative stress are major factors that promote the development of HFpEF pathologies. These signalling networks contribute to the development of the diseases. Inhibition and/or attenuation of these signalling networks also delays the onset of disease. In this review, we discuss the molecular mechanisms associated with the physiological responses to inflammation and oxidative stress and emphasize the nature of the contribution of most important cells to the development of HFpEF via increased inflammation and oxidative stress.

Dataset Information

Different Pathophysiology and Outcomes of Heart Failure With Preserved Ejection Fraction Stratified by K-Means Clustering.

Publications

Different Pathophysiology and Outcomes of Heart Failure With Preserved Ejection Fraction Stratified by K-Means Clustering.

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