Clinical Impact of the Volumetric Quantification of Ventricular Secondary Mitral Regurgitation by Three-Dimensional Echocardiography.

BACKGROUND: The assessment of ventricular secondary mitral regurgitation (v-SMR) severity through effective regurgitant orifice area (EROA) and regurgitant volume (RegVol) calculations using the proximal isovelocity surface area (PISA) method and the two-dimensional echocardiography volumetric method (2DEVM) is prone to underestimation. Accordingly, we sought to investigate the accuracy of the three-dimensional echocardiography volumetric method (3DEVM) and its association with outcomes in v-SMR patients. METHODS: We included 229 patients (70 ± 13 years, 74% men) with v-SMR. We compared EROA and RegVol calculated by the 3DEVM, 2DEVM, and PISA methods. The end point was a composite of heart failure hospitalization and death for any cause. RESULTS: After a mean follow-up of 20 ±11 months, 98 patients (43%) reached the end point. Regurgitant volume and EROA calculated by 3DEVM were larger than those calculated by 2DEVM and PISA. Using receiver operating characteristic curve analysis, both EROA (area under the curve, 0.75; 95% CI, 0.68-0.81; P = .008) and RegVol (AUC, 0.75; 95% CI, 0.68-0.82; P = .02) measured by 3DEVM showed the highest association with the outcome at 2 years compared to PISA and 2DEVM (P < .05 for all). Kaplan-Meier analysis demonstrated a significantly higher rate of events in patients with EROA ≥ 0.3 cm2 (cumulative survival at 2 years: 28% ± 7% vs 32% ± 10% vs 30% ± 11%) and RegVol ≥ 45 mL (cumulative survival at 2 years: 21% ± 7% vs 24% ± 13% vs 22% ± 10%) by 3DEVM compared to those by PISA and 2DEVM, respectively. In Cox multivariable analysis, 3DEVM EROA remained independently associated with the end point (hazard ratio, 1.02, 95% CI, 1.00-1.05; P = .02). The model including EROA by 3DEVM provided significant incremental value to predict the combined end point compared to those using 2DEVM (net reclassification index = 0.51, P = .003; integrated discrimination index = 0.04, P = .014) and PISA (net reclassification index = 0.80, P < .001; integrated discrimination index = 0.06, P < .001). CONCLUSIONS: Effective regurgitant orifice area and RegVol calculated by 3DEVM were independently associated with the end point, improving the risk stratification of patients with v-SMR compared to the 2DEVM and PISA methods.

Incremental Value of Right Atrial Strain Analysis to Predict Atrial Fibrillation Recurrence After Electrical Cardioversion.

BACKGROUND: Although the assessment of left atrial (LA) mechanics has been reported to refine atrial fibrillation (AF) risk prediction, it doesn't completely predict AF recurrence. The potential added role of right atrial (RA) function in this setting is unknown. Accordingly, this study sought to evaluate the added value of RA longitudinal reservoir strain (RASr) for the prediction of AF recurrence after electrical cardioversion (ECV). METHODS: We retrospectively studied 132 consecutive patients with persistent AF who underwent elective ECV. Complete two-dimensional and speckle-tracking echocardiography analyses of LA and RA size and function were obtained in all patients before ECV. The end point was AF recurrence. RESULTS: During a 12-month follow-up, 63 patients (48%) showed AF recurrence. Both LASr and RASr were significantly lower in patients experiencing AF recurrence than in patients with persistent sinus rhythm (LASr, 10% ± 6% vs 13% ± 7%; RASr, 14% ± 10% vs 20% ± 9%, respectively; P < .001 for both). Right atrial longitudinal reservoir strain (area under the curve = 0.77; 95% CI, 0.69-0.84; P < .0001) was more strongly associated with the recurrence of AF after ECV than LASr (area under the curve = 0.69; 95% CI, 0.60-0.77; P < .0001). Kaplan-Meier curves showed that patients with both LASr ≤ 10% and RASr ≤ 15% had a significantly increased risk for AF recurrence (log-rank, P < .001). However, at multivariable Cox regression, RASr (hazard ratio, 3.26; 95% CI, 1.73-6.13; P < .001) was the only parameter independently associated with AF recurrence. Right atrial longitudinal reservoir strain was more strongly associated with the occurrence of AF relapse after ECV than LASr, and LA and RA volumes. CONCLUSION: Right atrial longitudinal reservoir strain was independently and more strongly associated than LASr with AF recurrence after elective ECV. This study highlights the importance of assessing the functional remodeling of both the RA and LA in patients with persistent AF.

Association of outcome with left ventricular volumes and ejection fraction measured with two- and three-dimensional echocardiography in patients referred for routine, clinically indicated studies.

Objectives: We sought to analyze if left ventricular (LV) volumes and ejection fraction (EF) measured by three-dimensional echocardiography (3DE) have incremental prognostic value over measurements obtained from two-dimensional echocardiography (2DE) in patients referred to a high-volume echocardiography laboratory for routine, clinically-indicated studies. Methods: We measured LV volumes and EF using both 2DE and 3DE in 725 consecutive patients (67% men; 59 ± 18 years) with various clinical indications referred for a routine clinical study. Results: LV volumes were significantly larger, and EF was lower when measured by 3DE than 2DE. During follow-up (3.6 ± 1.2 years), 111 (15.3%) all-cause deaths and 248 (34.2%) cardiac hospitalizations occurred. Larger LV volumes and lower EF were associated with worse outcome independent of age, creatinine, hemoglobin, atrial fibrillation, and ischemic heart diseases). In stepwise Cox regression analyses, the associations of both death and cardiac hospitalization with clinical data (CD: age, creatinine, hemoglobin, atrial fibrillation, and ischemic heart disease) whose Harrel's C-index (HC) was 0.775, were augmented more by the LV volumes and EF obtained by 3DE than by 2DE parameters. The association of CD with death was not affected by LV end-diastolic volume (EDV) either measured by 2DE or 3DE. Conversely, it was incremented by 3DE LVEF (HC = 0.84, p < 0.001) more than 2DE LVEF (HC = 0.814, p < 0.001). The association of CD with the composite endpoint (HC = 0.64, p = 0.002) was augmented more by 3DE LV EDV (HC = 0.786, p < 0.001), end-systolic volume (HC = 0.801, p < 0.001), and EF (HC = 0.84, p < 0.001) than by the correspondent 2DE parameters (HC = 0.786, HC = 0.796, and 0.84, all p < 0.001) In addition, partition values for mild, moderate and severe reduction of the LVEF measured by 3DE showed a higher discriminative power than those measured by 2DE for cardiac death (Log-Rank: χ2 = 98.3 vs. χ2 = 77.1; p < 0.001). Finally, LV dilation defined according to the 3DE threshold values showed higher discriminatory power and prognostic value for death than when using 2DE reference values (3DE LVEDV: χ2 = 15.9, p < 0.001 vs. χ2 = 10.8, p = 0.001; 3DE LVESV: χ2 = 24.4, p < 0.001 vs. χ2 = 17.4, p = 0.001). Conclusion: In patients who underwent routine, clinically-indicated echocardiography, 3DE LVEF and ESV showed stronger association with outcome than the corresponding 2DE parameters.

Learning in realistic networks of spiking neurons and spike-driven plastic synapses.

We have used simulations to study the learning dynamics of an autonomous, biologically realistic recurrent network of spiking neurons connected via plastic synapses, subjected to a stream of stimulus-delay trials, in which one of a set of stimuli is presented followed by a delay. Long-term plasticity, produced by the neural activity experienced during training, structures the network and endows it with active (working) memory, i.e. enhanced, selective delay activity for every stimulus in the training set. Short-term plasticity produces transient synaptic depression. Each stimulus used in training excites a selective subset of neurons in the network, and stimuli can share neurons (overlapping stimuli). Long-term plasticity dynamics are driven by presynaptic spikes and coincident postsynaptic depolarization; stability is ensured by a refresh mechanism. In the absence of stimulation, the acquired synaptic structure persists for a very long time. The dependence of long-term plasticity dynamics on the characteristics of the stimulus response (average emission rates, time course and synchronization), and on the single-cell emission statistics (coefficient of variation) is studied. The study clarifies the specific roles of short-term synaptic depression, NMDA receptors, stimulus representation overlaps, selective stimulation of inhibition, and spike asynchrony during stimulation. Patterns of network spiking activity before, during and after training reproduce most of the in vivo physiological observations in the literature.

Mean field and capacity in realistic networks of spiking neurons storing sparsely coded random memories.

Mean-field (MF) theory is extended to realistic networks of spiking neurons storing in synaptic couplings of randomly chosen stimuli of a given low coding level. The underlying synaptic matrix is the result of a generic, slow, long-term synaptic plasticity of two-state synapses, upon repeated presentation of the fixed set of the stimuli to be stored. The neural populations subtending the MF description are classified by the number of stimuli to which their neurons are responsive (multiplicity). This involves 2p + 1 populations for a network storing p memories. The computational complexity of the MF description is then significantly reduced by observing that at low coding levels (f), only a few populations remain relevant: the population of mean multiplicity - pf and those of multiplicity of order square root pf around the mean. The theory is used to produce (predict) bifurcation diagrams (the onset of selective delay activity and the rates in its various stationary states) and to compute the storage capacity of the network (the maximal number of single items used in training for each of which the network can sustain a persistent, selective activity state). This is done in various regions of the space of constitutive parameters for the neurons and for the learning process. The capacity is computed in MF versus potentiation amplitude, ratio of potentiation to depression probability and coding level f. The MF results compare well with recordings of delay activity rate distributions in simulations of the underlying microscopic network of 10,000 neurons.