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Gradient variability in hypertrophic cardiomyopathy: New insights from computer‐assisted, high fidelity, rest and exercise hemodynamic analysis

OBJECTIVES: This study examines the intrapatient variability in peak instantaneous left ventricular outflow tract (LVOT) gradients and aortic pulse pressures during rest, exercise, and after ventricular ectopy. BACKGROUND: Although the variability in LVOT gradients in patients with hypertrophic card...

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Detalles Bibliográficos
Autores principales: Bauch, Terry D., Smith, Alexandra J., Murgo, Joseph P., Watts, James A., Rubal, Bernard J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6618132/
https://www.ncbi.nlm.nih.gov/pubmed/30474252
http://dx.doi.org/10.1002/ccd.27998
Descripción
Sumario:OBJECTIVES: This study examines the intrapatient variability in peak instantaneous left ventricular outflow tract (LVOT) gradients and aortic pulse pressures during rest, exercise, and after ventricular ectopy. BACKGROUND: Although the variability in LVOT gradients in patients with hypertrophic cardiomyopathy (HCM) is well known, the predictors of such variation are not. We hypothesized that quantitative invasive analysis of gradient variation could identify useful predictors of maximal gradients. METHODS: Variability in continuously recorded, high‐fidelity left ventricular and aortic pressure waveforms were evaluated by computer‐assisted analysis in the resting state (N = 659 beats) and during supine exercise (N = 379 beats) in a symptomatic patient with a resting LVOT gradient >30 mmHg and frequent ventricular ectopy. RESULTS: At rest, the peak left ventricular and aortic pressures at the time of the peak instantaneous LVOT gradient for all sinus and postectopic beats followed consistent regression slopes characterizing the potential energy loss between the LV cavity and aorta. During exercise, similar regression slopes were identified, and these converged with the resting slopes at the point of the maximal measured LVOT gradient. Component analysis of the LVOT gradient suggests that resting beat‐to‐beat variability provides information similar to post‐ectopic pressures for predicting maximal gradients in obstructive‐variant HCM. CONCLUSIONS: Our study suggests that computer‐assisted analysis of hemodynamic variability in HCM may prove useful in characterizing the severity of obstruction. Further study is warranted to confirm the reproducibility and utility of this finding in a population with clinically significant exercise‐induced gradients.