Paolo Marino

Dyspnea in older subjects and patients with HFpEF is usually attributed to elevated LV filling pressures caused by reduced end-diastolic compliance. This study demonstrates that during exercise, slow early diastolic relaxation and reduced ventricular suction limit increments in early diastolic filling and impair stroke volume reserve, thereby reducing exercise capacity. Lowering late systolic pressure and augmenting early diastolic filling may be important targets for pharmacologic therapy to reduce dyspnea.

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Three‐dimensional echocardiography can elucidate the phasic functions of the left atrium if a simultaneous acquisition of a pyramidal full‐volume dataset, as gathered from the apical window and containing the entire left atrial and left ventricular cardiac sections, is obtained. Hence, conduit can be quantified as the integral of net, diastolic, instantaneous difference between synchronized atrial and ventricular volume curves, beginning at minimum ventricular cavity volume and ending just before atrial contraction. Increased conduit can reflect increased downstream suction, as conduit would track the apex‐to‐base intracavitary pressure gradient existing, in early diastole, within the single chamber formed by the atrium and the ventricle, when the mitral valve is open. Such a gradient increases in response to adrenergic stimulation or during exercise and mediates an increment in passive flow during early diastole, with the ventricle being filled from the atrial reservoir and, simultaneously, from blood drawn from the pulmonary veins. In this context conduit, and even more conduit flow rate, expressed in ml/sec, can be viewed as an indirect marker of left ventricular relaxation.It is well known, however, that a large amount of conduit (in relative terms) is also supposed to contribute to LV stroke volume in conditions of increased resistance to LV filling, when diastolic function significantly worsens. Stiffening of the atrio‐ventricular complex implies increments in LA pressure more pronounced in late systole, causing markedly elevated “v” waves, independently of the presence of mitral insufficiency. The combination of increased atrio‐ventricular stiffness and conduit flow is associated with an elevation of the right ventricular pulsatile relative to resistive load that negatively impacts on exercise capacity and survival in these patients.Atrial conduit is an “intriguing” parameter that conveys a noninvasive picture of the complex atrioventricular coupling condition in diastole and its backward effects on the right side of the heart and the pulmonary circulation. Given the easiness associated with its correctly performed quantification in the imaging laboratory, I am sure that conduit will survive the competitive access to the list of valuable parameters capable of deciphering, although not necessarily simplifying, the complex diastolic scenario in health and disease.

Aims In healthy subjects, adrenergic stimulation augments left ventricular (LV) long-axis shortening and lengthening, and increases left atrial (LA) to LV intracavitary pressure gradients in early diastole. Lower increments are observed in patients with heart failure with preserved ejection fraction (HFpEF). We hypothesized that exercise in HFpEF would further impair passive LV filling in early-mid diastole, during conduit flow from pulmonary veins. Methods and results Twenty HFpEF patients (67.8 ± 9.8 years; 11 women), diagnosed using 2007 ESC recommendations, underwent ramped semi-supine bicycle exercise to submaximal target heart rate (∼100 bpm) or symptoms. Seventeen asymptomatic subjects (64.3 ± 8.9 years; 7 women) were controls. Simultaneous LA and LV volumes were measured from pyramidal 3D-echocardiographic full-volume datasets acquired from an apical window at baseline and during stress, together with brachial arterial pressure. LA conduit flow was computed from the increase in LV volume from its minimum at end-systole to the last frame before atrial contraction (onset of the P wave), minus the reduction in LA volume during the same time interval; the difference was integrated and expressed as average flow rate, according to a published formula. The slope of single-beat preload recruitable stroke work (PRSW) quantified LV inotropic state. 3D LV torsion (rotation of the apex minus rotation of the base divided by LV length) was also measurable, both at rest and during stress, in 10 HFpEF patients and 4 controls. There were divergent responses in conduit flow rate, which increased by 40% during exercise in controls (+17.8 ± 37.3 mL/s) but decreased by 18% in patients with HFpEF (−9.6 ± 42.3 mL/s) (P = 0.046), along with congruent changes (+1.77 ± 1.13°/cm vs. −1.94 ± 2.73°/cm) in apical torsion (P = 0.032). Increments of conduit flow rate and apical torsion during stress correlated with changes in PRSW slope (P = 0.003 and P = 0.006, respectively). Conclusions In HFpEF, conduit flow rate decreases when diastolic dysfunction develops during exercise, in parallel with changes in LV inotropic state and torsion, contributing to impaired stroke volume reserve. Conduit flow is measurable using 3D-echocardiographic full-volume atrio-ventricular datasets, and as a marker of LV relaxation can contribute to the diagnosis of HFpEF.

Aims: To assess if left atrial phasic function characteristics modulate functional capacity/survival by impacting on the pulsatile component of right ventricular (RV) afterload, as represented by pulmonary arterial compliance (PAC). Materials and methods: Sixty heart failure patients (67 ± 11 years, ejection fraction 39 ± 11%, range 20--62%) underwent 6 min walk test (6MWT) and 3D transthoracic echocardiography. Left atrial conduit was computed off-line, gathering simultaneous real-time 3D multibeats (six cycles) left atrial and left ventricular (LV) volume curves, with conduit (time) = [LV (time) − LV minimum volume] − [left atrial maximum volume − left atrial (time)], expressed as % LV stroke volume. Atrial stiffness (K _la) was computed using noninvasively assessed wedge pressure divided by left atrial reservoir (maximum − minimum) volume. PAC was obtained as ratio between RV stroke volume, obtained as pulsed Doppler RV outflow tract envelope_∗cross-sectional area, and pulmonary pulse pressure, obtained by transforming tricuspid regurgitant velocity in millimetres of mercury and considering diastolic pulmonary as a fixed fraction of systolic pressure. Results: Conduit averaged 34 ± 12%, PAC 3.1 ± 1.1 ml/mmHg, 6MWT 404 ± 154 m. Conduit was independent of LV volumes and ejection fraction, showing a direct dependence on noninvasive K _la (r = 0.56; P < 0.001). Dividing patients into tertiles according to 6MWT and to PAC, the largest conduit fraction was associated with the lowest functional capacity (P < 0.001) and most deranged PAC (P < 0.001), respectively, suggesting outmost RV haemodynamic burden. Tertiles of conduit predicted survival (P = 0.01). Conclusion: Conduit depends on noninvasively assessed K _la and appears to be increased in heart failure patients with lowest capacity and worst survival, likely as RV pulsatile afterload, as reflected by PAC, is highest in these individuals.

Background: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome for which clear evidence of effective therapies is lacking. Understanding which factors determine this heterogeneity may be helped by better phenotyping. An unsupervised statistical approach applied to a large set of biomarkers may identify distinct HFpEF phenotypes. Methods: Relevant proteomic biomarkers were analyzed in 392 HFpEF patients included in Metabolic Road to Diastolic HF (MEDIA-DHF). We performed an unsupervised cluster analysis to define distinct phenotypes. Cluster characteristics were explored with logistic regression. The association between clusters and 1-year cardiovascular (CV) death and/or CV hospitalization was studied using Cox regression. Results: Based on 415 biomarkers, we identified 2 distinct clusters. Clinical variables associated with cluster 2 were diabetes, impaired renal function, loop diuretics and/or betablockers. In addition, 17 biomarkers were higher expressed in cluster 2 vs. 1. Patients in cluster 2 vs. those in 1 experienced higher rates of CV death/CV hospitalization (adj. HR 1.93, 95% CI 1.12–3.32, p = 0.017). Complex-network analyses linked these biomarkers to immune system activation, signal transduction cascades, cell interactions and metabolism. Conclusion: Unsupervised machine-learning algorithms applied to a wide range of biomarkers identified 2 HFpEF clusters with different CV phenotypes and outcomes. The identified pathways may provide a basis for future research.

Aortic stenosis is a frequent valvular disease, with transcatheter aortic valve implantation (TAVI) being performed when surgical replacement is at increased risk. However, TAVI-induced effects on myocardial efficiency are unknown. We aimed to investigate changes in LV mechano-energetic pre-/post-TAVI and their prognostic impact.