Key result
Resting beat-to-beat hemodynamic variability matches post-ectopic pressures for predicting peak LVOT gradients in HCM.
Why the study?
Although LVOT gradient variability in HCM is well known, predictors of such variation are not.
Case Report (n=1)
No
Mean Difference: 68
p-value: p=<0.001
Computer-assisted analysis of beat-to-beat hemodynamic variability in a single HCM patient suggests that resting variability may predict maximal exercise-induced LVOT gradients.
Resting beat-to-beat variability may approximate post-ectopic LVOT gradient assessment in HCM; hypothesis-generating from one case and requires validation.
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.
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Bauch et al. (2018) conducted a case report in Hypertrophic cardiomyopathy (n=1). Ventricular ectopy (post-PVC beats) vs. Pre-ectopic sinus beats was evaluated on Change in peak instantaneous LVOT gradient post-PVC at rest (68 mmHg increase, p=<0.001). In a patient with hypertrophic cardiomyopathy, resting beat-to-beat hemodynamic variability provided information similar to post-ectopic pressures for predicting maximal left ventricular outflow tract gradients.
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