Dataset Information

Age-specific diastolic dysfunction improves prediction of symptomatic heart failure by Stage B heart failure.

ABSTRACT:

Aims

We investigated whether addition of diastolic dysfunction (DD) and longitudinal strain (LS) to Stage B heart failure (SBHF) criteria (structural or systolic abnormality) improves prediction of symptomatic HF in participants of the SCReening Evaluation of the Evolution of New Heart Failure study, a self-selected population at increased cardiovascular disease risk recruited from members of a health insurance fund in Melbourne and Shepparton, Australia. Both American Society of Echocardiography and European Association of Cardiovascular Imaging (ASE/EACVI) criteria and age-specific Atherosclerosis Risk in Communities (ARIC) study criteria, for SBHF and DD, and ARIC criteria for abnormal LS, were examined.

Methods and results

Inclusion criteria were age ≥60 years with one or more of self-reported ischaemic or other heart disease, irregular or rapid heart rhythm, cerebrovascular disease, renal impairment, or treatment for hypertension or diabetes for ≥2 years. Exclusion criteria were known HF, or ejection fraction <50% or >mild valve abnormality detected on previous echocardiography or other imaging. Echocardiography was performed in 3190 participants who were followed for a median of 3.9 (interquartile range: 3.4, 4.5) years after echocardiography. Symptomatic HF was diagnosed in 139 participants at a median of 3.1 (interquartile range: 2.1, 3.9) years after echocardiography. ARIC structural, systolic, and diastolic abnormalities predicted HF in univariate and multivariable proportional hazards analyses, whereas ASE/EACVI structural and systolic, but not diastolic, abnormalities predicted HF. ARIC and ASE/EACVI SBHF criteria predicted HF with sensitivities of 81% and 55%, specificities of 39% and 76%, and C statistics of 0.60 (95% confidence interval: 0.57, 0.64) and 0.66 (0.61, 0.71), respectively. Adding ARIC DD to SBHF increased sensitivity to 94% with specificity of 24% and C statistic of 0.59 (0.57, 0.61), whereas addition of ASE/EACVI DD to SBHF increased sensitivity to 97% but reduced specificity to 9% and the C statistic to 0.52 (0.50, 0.54, P < 0.0001). Addition of LS to ARIC or ASE/EACVI SBHF criteria had minimal impact on prediction of HF.

Conclusions

Age-specific ARIC DD criteria, but not ASE/EACVI DD criteria, predicted symptomatic HF, and addition of age-specific ARIC DD criteria to ARIC SBHF criteria improved prediction of symptomatic HF in asymptomatic individuals with cardiovascular disease risk factors. Addition of LS to ASE/EACVI or ARIC SBHF criteria did not improve prediction of symptomatic HF.

SUBMITTER: Coller JM

PROVIDER: S-EPMC6676278 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Age-specific diastolic dysfunction improves prediction of symptomatic heart failure by Stage B heart failure.

Coller Jennifer M JM Gong Fei Fei FF McGrady Michele M Jelinek Michael V MV Castro Julian M JM Boffa Umberto U Shiel Louise L Liew Danny D Stewart Simon S Krum Henry H Reid Christopher M CM Prior David L DL Campbell Duncan J DJ

ESC heart failure 20190515 4

<h4>Aims</h4>We investigated whether addition of diastolic dysfunction (DD) and longitudinal strain (LS) to Stage B heart failure (SBHF) criteria (structural or systolic abnormality) improves prediction of symptomatic HF in participants of the SCReening Evaluation of the Evolution of New Heart Failure study, a self-selected population at increased cardiovascular disease risk recruited from members of a health insurance fund in Melbourne and Shepparton, Australia. Both American Society of Echocar ...[more]

PMID: 31094087

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Project description:Aldosterone infusion results in left ventricular hypertrophy (LVH) and hypertension and may involve profibrotic and proinflammatory mechanisms. In turn, hypertension is the major cause of diastolic heart failure (HF). Adiponectin, an adipose-derived plasma protein, exerts antiinflammatory and anti-hypertrophic effects and is implicated in the development of hypertension and systolic HF. We thus tested the hypothesis that hypoadiponectinemia in aldosterone-induced hypertension exacerbated cardiac remodeling and diastolic HF. Wild-type (WT) or adiponectin-deficient (APNKO) mice underwent saline or aldosterone infusion and uninephrectomy and were fed 1% salt water for 4 wk. Blood pressure was increased in aldosterone-infused WT (132 +/- 2 vs. 109 +/- 3 mm Hg; P < 0.01) and further augmented in APNKO mice (140 +/- 3 mm Hg; P < 0.05 vs. aldosterone-infused WT). LVH was increased in aldosterone-infused WT vs. WT mice (LV/body weight ratio, 4.8 +/- 0.2 vs. 4.1 +/- 0.2 mg/g) and further increased in aldosterone-infused APNKO mice (LV/body weight ratio, 6.0 +/- 0.4 mg/g). Left ventricular ejection fraction was not decreased in either aldosterone-infused WT or APNKO hearts. Pulmonary congestion however was worse in APNKO mice (P < 0.01). The ratio of early ventricular filling over late ventricular filling (E/A) and the ratio of mitral peak velocity of early filling to early diastolic mitral annular velocity (E/e'), measures of diastolic function, were increased in aldosterone-infused WT hearts and further increased in APNKO hearts (P < 0.05 for both). Renal function and cardiac fibrosis were no different between both aldosterone-infused groups. Aldosterone increased matrix metalloproteinase-2 expression in WT hearts (P < 0.05 vs. WT and P < 0.01 vs. APNKO). Myocardial atrial natriuretic peptide, interferon-gamma, and TNF-alpha expression were increased in aldosterone-infused WT hearts. Expression of these proteins was further increased in aldosterone-infused APNKO hearts. Therefore, hypoadiponectinemia in hypertension-induced diastolic HF exacerbates LVH, diastolic dysfunction, and diastolic HF. Whether or not adiponectin replacement prevents the progression to diastolic HF will warrant further study.

Project description:Background: Discriminating between different patterns of diastolic dysfunction in heart failure (HF) is still challenging. We tested the hypothesis that an unsupervised machine learning algorithm would detect heterogeneity in diastolic function and improve risk stratification compared with recommended consensus criteria. Methods: This study included 279 consecutive patients aged 24-97 years old with clinically stable HF referred for echocardiographic assessment, in whom diastolic variables were measured according to the current guidelines. Cluster analysis was undertaken to identify homogeneous groups of patients with similar profiles of the variables. Sequential Cox models were used to compare cluster-based classification with guidelines-based classification for predicting clinical outcomes. The primary endpoint was hospitalization for worsening HF. Results: The analysis identified three clusters with distinct properties of diastolic function that shared similarities with guidelines-based classification. The clusters were associated with brain natriuretic peptide level (p < 0.001), hemoglobin concentration (p = 0.017) and estimated glomerular filtration rate (p = 0.001). During a mean follow-up period of 2.6 ± 2.0 years, 62 patients (22%) experienced the primary endpoint. Cluster-based classification predicted events with a hazard ratio 1.68 (p = 0.019) that was independent from and incremental to the Meta-analysis Global Group in Chronic Heart Failure (MAGGIC) risk score for HF, and from left ventricular end-diastolic volume and global longitudinal strain, whereas guidelines-based classification did not retain its independent prognostic value (hazard ratio = 1.25, p = 0.202). Conclusion: Machine learning can identify patterns of diastolic function that better stratify the risk for decompensation than the current consensus recommendations in HF. Integrating this data-driven phenotyping may help in refining prognostication and optimizing treatment.

Dataset Information

Age-specific diastolic dysfunction improves prediction of symptomatic heart failure by Stage B heart failure.

Aims

Methods and results

Conclusions

Publications

Age-specific diastolic dysfunction improves prediction of symptomatic heart failure by Stage B heart failure.

Similar Datasets

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