Literature DB >> 21440868

Decreased cardiac functional reserve in heart failure with preserved systolic function.

Holly S Norman1, James Oujiri, Shane J Larue, Carrie B Chapman, Kenneth B Margulies, Nancy K Sweitzer.   

Abstract

BACKGROUND: Heart failure in patients with preserved left ventricular systolic function (HFpEF) is a prevalent disease characterized by exercise intolerance with poorly understood pathophysiology. We hypothesized that recruitable contractility is impaired in HFpEF, accounting for the appearance of symptoms with exertion. METHODS AND
RESULTS: Echocardiographic analysis of myocardial performance was performed at baseline and after a modified dobutamine protocol (max dose 16 μg/kg/min) in participants with known HFpEF and age- and gender-matched controls. The primary outcome variable was change in contractile reserve, measured as a change in ejection fraction (EF). Recruitable contractility was decreased in HFpEF participants compared with control subjects (HFpEF 0.4 ± 1.9% vs control 19.0 ± 1.4%; P < .001). During dobutamine infusion, velocities increased in control participants but remained unchanged in the HFpEF group, yielding a significant difference between groups (P < .05) for both longitudinal displacement and velocity.
CONCLUSIONS: Patients with HFpEF have an impaired contractile response to adrenergic stimulation. The blunted response to adrenergic stimulation in the HFpEF group suggests that these patients may be unable to respond to periods of increased cardiac demand. This inability to increase contractility appropriately suggests abnormalities of systolic function in this disease and may contribute to exertional intolerance in HFpEF.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 21440868      PMCID: PMC3073553          DOI: 10.1016/j.cardfail.2010.11.004

Source DB:  PubMed          Journal:  J Card Fail        ISSN: 1071-9164            Impact factor:   5.712


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8.  Left ventricular systolic performance, function, and contractility in patients with diastolic heart failure.

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8.  Novel Wearable Seismocardiography and Machine Learning Algorithms Can Assess Clinical Status of Heart Failure Patients.

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