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Ventricular stroke work and vascular impedance refine the characterization of patients with aortic stenosis.

ABSTRACT: Aortic stenosis (AS) management is classically guided by symptoms and valvular metrics. However, the natural history of AS is dictated by coupling of the left ventricle, aortic valve, and vascular system. We investigated whether metrics of ventricular and vascular state add to the appreciation of AS state above valve gradient alone. Seventy patients with severe symptomatic AS were prospectively followed from baseline to 30 days after transcatheter aortic valve replacement (TAVR). Quality of life (QOL) was assessed using the Kansas City Cardiomyopathy Questionnaire. Left ventricular stroke work (SWLV) and vascular impedance spectrums were calculated noninvasively using in-house models based on central blood pressure waveforms, along with hemodynamic parameters from echocardiograms. Patients with higher preprocedural SWLV and lower vascular impedance were more likely to experience improved QOL after TAVR. Patients fell into two categories: those who did and those who did not exhibit increase in blood pressure after TAVR. In patients who developed hypertension (19%), vascular impedance increased and SWLV remained unchanged (impedance at zeroth harmonic: Z 0, from 3964.4 to 4851.8 dyne·s/cm3, P = 0.039; characteristic impedance: Z c, from 376.2 to 603.2 dyne·s/cm3, P = 0.033). SWLV dropped only in patients who did not develop new hypertension after TAVR (from 1.58 to 1.26 J; P < 0.001). Reduction in valvular pressure gradient after TAVR did not predict change in SWLV (r = 0.213; P = 0.129). Reduction of SWLV after TAVR may be an important metric in management of AS, rather than relying solely on the elimination of transvalvular pressure gradients.

SUBMITTER: Ben-Assa E

PROVIDER: S-EPMC7401937 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Ventricular stroke work and vascular impedance refine the characterization of patients with aortic stenosis.

Ben-Assa Eyal E Brown Jonathan J Keshavarz-Motamed Zahra Z de la Torre Hernandez Jose M JM Leiden Benjamin B Olender Max M Kallel Faouzi F Palacios Igor F IF Inglessis Ignacio I Passeri Jonathan J JJ Shah Pinak B PB Elmariah Sammy S Leon Martin B MB Edelman Elazer R ER

Science translational medicine 20190901 509

Aortic stenosis (AS) management is classically guided by symptoms and valvular metrics. However, the natural history of AS is dictated by coupling of the left ventricle, aortic valve, and vascular system. We investigated whether metrics of ventricular and vascular state add to the appreciation of AS state above valve gradient alone. Seventy patients with severe symptomatic AS were prospectively followed from baseline to 30 days after transcatheter aortic valve replacement (TAVR). Quality of life ...[more]

PMID: 31511424

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Project description:Importance:Clinical practice guidelines currently endorse a reliance on clinical symptoms of overt left ventricular (LV) failure to time aortic valve replacement for severe aortic stenosis; however, delayed aortic valve replacement can result in irreversible LV injury and adverse outcomes. Blood metabolomic signatures possess prognostic value in heart failure; this study assesses whether they are informative in aortic stenosis. Objective:To evaluate the value of metabolomic signatures in reflecting the extent of maladaptive LV remodeling in patients with end-stage aortic stenosis undergoing transcatheter aortic valve replacement, and to assess whether this procedure reverses metabolomic aberrations. Design, Setting, and Participants:This study of 44 patients with symptomatic severe aortic stenosis who underwent transfemoral transcatheter aortic valve replacement at a single-center tertiary care hospital. Liquid chromatography-mass spectrometry-based metabolomic profiling was performed on blood samples collected before and 24 hours after the procedure, and analyses were conducted to identify metabolites related to the measures of LV remodeling. Main Outcomes and Measures:We evaluated LV ejection fraction, LV mass index, and relative wall thickness, as well as levels of the acylcarnitines C16, C18:1, C18:2, C18, C26, choline, and kynurenine. Results:We enrolled 44 patients with severe aortic stenosis with a mean (SD) age of 81.9 (8.5) years, of whom 23 (52%) were women. The mean (SD) LV ejection fraction was 56.7% (18.2%), mean (SD) LV mass index was 117.3 (41.4) g/m2, and relative wall thickness was 0.53 (0.14). The mean β values of acylcarnitines C16, C18:1, C18:2, C18, and C26 were independently associated with LV mass index (C16: mean, 19.24; 95% CI, 5.48-33.01; P = .008; C18:1: mean, 26.18; 95% CI, 14.04-38.32; P < 1.0 × 10-4; C18:2: mean, 17.42; 95% CI, 3.40-31.43; P = .02; C18: mean, 25.25; 95% CI, 10.91-39.58; P = .001; C26: mean, 19.93; 95% CI, 4.41-35.45; P = .01), even after adjustments for age, sex, diabetes status, renal function, and B-type natriuretic peptide (BNP). Circulating levels of C18:2 acylcarnitine were associated with LV ejection fraction before and after multivariable adjustment (mean, -6.11; 95% CI, -10.88 to 1.34; P = .01). Blood metabolite levels did not independently relate to relative wall thickness. Within 24 hours of transcatheter aortic valve replacement, circulating levels of C16 decreased by 30.2% (P = 7.3 × 10-6), C18:1 by 42.7% (P = 3.7 × 10-8), C18:2 by 37.3% (P = 5.1 × 10-6), and C18 by 38.3% (P = 3.4 × 10-5). Conclusions and Relevance:In symptomatic patients with severe aortic stenosis undergoing transcatheter aortic valve replacement, circulating levels of long-chain acylcarnitines were independently associated with measures of maladaptive LV remodeling, and metabolic perturbations lessened after procedure completion. Further efforts are needed to determine the clinical applicability of these novel biomarkers.

Dataset Information

Ventricular stroke work and vascular impedance refine the characterization of patients with aortic stenosis.

Publications

Ventricular stroke work and vascular impedance refine the characterization of patients with aortic stenosis.

Similar Datasets

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