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Phenomapping for novel classification of heart failure with preserved ejection fraction.

ABSTRACT: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous clinical syndrome in need of improved phenotypic classification. We sought to evaluate whether unbiased clustering analysis using dense phenotypic data (phenomapping) could identify phenotypically distinct HFpEF categories.We prospectively studied 397 patients with HFpEF and performed detailed clinical, laboratory, ECG, and echocardiographic phenotyping of the study participants. We used several statistical learning algorithms, including unbiased hierarchical cluster analysis of phenotypic data (67 continuous variables) and penalized model-based clustering, to define and characterize mutually exclusive groups making up a novel classification of HFpEF. All phenomapping analyses were performed by investigators blinded to clinical outcomes, and Cox regression was used to demonstrate the clinical validity of phenomapping. The mean age was 65±12 years; 62% were female; 39% were black; and comorbidities were common. Although all patients met published criteria for the diagnosis of HFpEF, phenomapping analysis classified study participants into 3 distinct groups that differed markedly in clinical characteristics, cardiac structure/function, invasive hemodynamics, and outcomes (eg, phenogroup 3 had an increased risk of HF hospitalization [hazard ratio, 4.2; 95% confidence interval, 2.0-9.1] even after adjustment for traditional risk factors [P<0.001]). The HFpEF phenogroup classification, including its ability to stratify risk, was successfully replicated in a prospective validation cohort (n=107).Phenomapping results in a novel classification of HFpEF. Statistical learning algorithms applied to dense phenotypic data may allow improved classification of heterogeneous clinical syndromes, with the ultimate goal of defining therapeutically homogeneous patient subclasses.

SUBMITTER: Shah SJ

PROVIDER: S-EPMC4302027 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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Phenomapping for novel classification of heart failure with preserved ejection fraction.

Shah Sanjiv J SJ Katz Daniel H DH Selvaraj Senthil S Burke Michael A MA Yancy Clyde W CW Gheorghiade Mihai M Bonow Robert O RO Huang Chiang-Ching CC Deo Rahul C RC

Circulation 20141114 3

<h4>Background</h4>Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous clinical syndrome in need of improved phenotypic classification. We sought to evaluate whether unbiased clustering analysis using dense phenotypic data (phenomapping) could identify phenotypically distinct HFpEF categories.<h4>Methods and results</h4>We prospectively studied 397 patients with HFpEF and performed detailed clinical, laboratory, ECG, and echocardiographic phenotyping of the study participan ...[more]

PMID: 25398313

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Project description:AimsHeart failure (HF) with preserved ejection fraction (HFpEF) is a complex syndrome with a poor prognosis. Phenotyping is required to identify subtype-dependent treatment strategies. Phenotypes of Japanese HFpEF patients are not fully elucidated, whose obesity is much less than Western patients. This study aimed to reveal model-based phenomapping using unsupervised machine learning (ML) for HFpEF in Japanese patients.Methods and resultsWe studied 365 patients with HFpEF (left ventricular ejection fraction >50%) as a derivation cohort from the Nara Registry and Analyses for Heart Failure (NARA-HF), which registered patients with hospitalization by acute decompensated HF. We used unsupervised ML with a variational Bayesian-Gaussian mixture model (VBGMM) with common clinical variables. We also performed hierarchical clustering on the derivation cohort. We adopted 230 patients in the Japanese Heart Failure Syndrome with Preserved Ejection Fraction Registry as the validation cohort for VBGMM. The primary endpoint was defined as all-cause death and HF readmission within 5 years. Supervised ML was performed on the composite cohort of derivation and validation. The optimal number of clusters was three because of the probable distribution of VBGMM and the minimum Bayesian information criterion, and we stratified HFpEF into three phenogroups. Phenogroup 1 (n = 125) was older (mean age 78.9 ± 9.1 years) and predominantly male (57.6%), with the worst kidney function (mean estimated glomerular filtration rate 28.5 ± 9.7 mL/min/1.73 m2 ) and a high incidence of atherosclerotic factor. Phenogroup 2 (n = 200) had older individuals (mean age 78.8 ± 9.7 years), the lowest body mass index (BMI; 22.78 ± 3.94), and the highest incidence of women (57.5%) and atrial fibrillation (56.5%). Phenogroup 3 (n = 40) was the youngest (mean age 63.5 ± 11.2) and predominantly male (63.5 ± 11.2), with the highest BMI (27.46 ± 5.85) and a high incidence of left ventricular hypertrophy. We characterized these three phenogroups as atherosclerosis and chronic kidney disease, atrial fibrillation, and younger and left ventricular hypertrophy groups, respectively. At the primary endpoint, Phenogroup 1 demonstrated the worst prognosis (Phenogroups 1-3: 72.0% vs. 58.5% vs. 45%, P = 0.0036). We also successfully classified a derivation cohort into three similar phenogroups using VBGMM. Hierarchical and supervised clustering successfully showed the reproducibility of the three phenogroups.ConclusionsML could successfully stratify Japanese HFpEF patients into three phenogroups (atherosclerosis and chronic kidney disease, atrial fibrillation, and younger and left ventricular hypertrophy groups).

Project description:BACKGROUND:The role of coronary microvascular disease and its impact on functional and energetic reserve in heart failure with preserved ejection fraction (HFpEF) remains unclear. We hypothesized that in response to submaximal pharmacologic stress (dobutamine), patients with HFpEF have impairment in left ventricular (LV) myocardial mechanical (external work [EW]), energetic (myocardial O2 consumption [MVO2]), and myocardial blood flow (MBF) reserve. We further assessed whether coupling of MBF to EW is impaired in HFpEF and associated with compensatory increases or pathological decreases in myocardial O2 extraction. Lastly, we assessed whether coupling of MVO2 to EW (mechanical efficiency) was impaired in HFpEF. METHODS AND RESULTS:In prospectively enrolled patients with HFpEF (n=19) and age/sex-matched healthy controls (n=19), we performed 11C-acetate positron emission tomography assessing MVO2 and MBF at rest and during dobutamine infusion. EW was calculated as stroke volume (echo)×end-systolic pressure×heart rate. At rest, compared with controls, patients with HFpEF had higher LV EW, MVO2, and MBF. With dobutamine, LV EW, MVO2, and MBF increased in both HFpEF and controls; however, the magnitude of increases was significantly smaller in HFpEF. In both groups, MBF increased in relation to EW, but in HFpEF, the slope of the relationship was significantly smaller than in controls. Myocardial O2 extraction was increased in HFpEF. Mechanical efficiency was similar in HFpEF and controls. In a post hoc analysis, HFpEF patients with LV hypertrophy (n=10) had significant reductions in LV mechanical efficiency relative to controls. CONCLUSIONS:In HFpEF during submaximal dobutamine stress, there is myocardial mechanical-, energetic- and flow-reserve dysfunction with impaired coupling of blood flow to demand and slight increases in myocardial O2 extraction. These findings provide evidence that coronary microvascular dysfunction is present in HFpEF, limits O2 supply relative to demand, and is associated with reserve dysfunction.

Project description:Nitrates are commonly prescribed to enhance activity tolerance in patients with heart failure and a preserved ejection fraction. We compared the effect of isosorbide mononitrate or placebo on daily activity in such patients.In this multicenter, double-blind, crossover study, 110 patients with heart failure and a preserved ejection fraction were randomly assigned to a 6-week dose-escalation regimen of isosorbide mononitrate (from 30 mg to 60 mg to 120 mg once daily) or placebo, with subsequent crossover to the other group for 6 weeks. The primary end point was the daily activity level, quantified as the average daily accelerometer units during the 120-mg phase, as assessed by patient-worn accelerometers. Secondary end points included hours of activity per day during the 120-mg phase, daily accelerometer units during all three dose regimens, quality-of-life scores, 6-minute walk distance, and levels of N-terminal pro-brain natriuretic peptide (NT-proBNP).In the group receiving the 120-mg dose of isosorbide mononitrate, as compared with the placebo group, there was a nonsignificant trend toward lower daily activity (-381 accelerometer units; 95% confidence interval [CI], -780 to 17; P=0.06) and a significant decrease in hours of activity per day (-0.30 hours; 95% CI, -0.55 to -0.05; P=0.02). During all dose regimens, activity in the isosorbide mononitrate group was lower than that in the placebo group (-439 accelerometer units; 95% CI, -792 to -86; P=0.02). Activity levels decreased progressively and significantly with increased doses of isosorbide mononitrate (but not placebo). There were no significant between-group differences in the 6-minute walk distance, quality-of-life scores, or NT-proBNP levels.Patients with heart failure and a preserved ejection fraction who received isosorbide mononitrate were less active and did not have better quality of life or submaximal exercise capacity than did patients who received placebo. (Funded by the National Heart, Lung, and Blood Institute; ClinicalTrials.gov number, NCT02053493.).

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Phenomapping for novel classification of heart failure with preserved ejection fraction.

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Phenomapping for novel classification of heart failure with preserved ejection fraction.

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