BackgroundRight ventricular (RV) long-axis function is known to be depressed after cardiac surgery, but the mechanism is not known. We hypothesized that intraoperative transesophageal echocardiography could pinpoint the time at which this happens to help narrow the range of plausible mechanisms.MethodTransthoracic echocardiography was conducted in 33 patients before and after elective coronary artery bypass graft. In an intensively monitored cohort of 9 patients, we also monitored RV function intraoperatively using serial pulsed wave tissue Doppler (PW TD) transesophageal echocardiography.ResultsThere was no significant difference in myocardial velocities from the onset of the operation up to the beginning of pericardial incision, change in RV PW TD S′ velocities 3% ± 2% (P = not significant).Within the first 3 minutes of opening the pericardium, RV PW TD S′ velocities had reduced by 43% ± 17% (P < .001). At 5 minutes postpericardial incision, 2 minutes later, the velocities had more than halved, by 54% ± 11% (P < .0001). Velocities thereafter remained depressed throughout the operation, with final intraoperative S′ reduction being 61% ± 11% (P < .0001).One month after surgery, in the full 33-patient cohort, transthoracic echocardiogram data showed a 55% ± 12% (P < .0001) reduction in RV S′ velocities compared with preoperative values.ConclusionsMinute-by-minute monitoring during cardiac surgery reveals that, virtually, all the losses in RV systolic velocity occurs within the first 3 minutes after pericardial incision. Right ventricular long-axis reduction during coronary bypass surgery results not from cardiopulmonary bypass but rather from pericardial incision.
BackgroundLocalizing the origin of outflow tract ventricular tachycardias (OTVT) is hindered by lack of accuracy of electrocardiographic (ECG) algorithms and infrequent spontaneous premature ventricular complexes (PVCs) during electrophysiological studies.ObjectivesTo prospectively assess the performance of noninvasive electrocardiographic mapping (ECM) in the pre-/periprocedural localization of OTVT origin to guide ablation and to compare the accuracy of ECM with that of published ECG algorithms.MethodsPatients with symptomatic OTVT/PVCs undergoing clinically indicated ablation were recruited. The OTVT/PVC origin was mapped preprocedurally by using ECM, and 3 published ECG algorithms were applied to the 12-lead ECG by 3 blinded electrophysiologists. Ablation was guided by using ECM. The OTVT/PVC origin was defined as the site where ablation caused arrhythmia suppression. Acute success was defined as abolition of ectopy after ablation. Medium-term success was defined as the abolition of symptoms and reduction of PVC to less than 1000 per day documented on Holter monitoring within 6 months.ResultsIn 24 patients (mean age 50 ± 18 years) recruited ECM successfully identified OTVT/PVC origin in 23/24 (96%) (right ventricular outflow tract, 18; left ventricular outflow tract, 6), sublocalizing correctly in 100% of this cohort. Acute ablation success was achieved in 100% of the cases with medium-term success in 22 of 24 patients. PVC burden reduced from 21,837 ± 23,241 to 1143 ± 4039 (P < .0001). ECG algorithms identified the correct chamber of origin in 50%–88% of the patients and sublocalized within the right ventricular outflow tract (septum vs free-wall) in 37%–58%.ConclusionsECM can accurately identify OTVT/PVC origin in the left and the right ventricle pre- and periprocedurally to guide catheter ablation with an accuracy superior to that of published ECG algorithms.
Impact of variability in the measured parameter is rarely considered in designing clinical protocols for optimization of atrioventricular (AV) or interventricular (VV) delay of cardiac resynchronization therapy (CRT). In this article, we approach this question quantitatively using mathematical simulation in which the true optimum is known and examine practical implications using some real measurements. We calculated the performance of any optimization process that selects the pacing setting which maximizes an underlying signal, such as flow or pressure, in the presence of overlying random variability (noise). If signal and noise are of equal size, for a 5-choice optimization (60, 100, 140, 180, 220 ms), replicate AV delay optima are rarely identical but rather scattered with a standard deviation of 45 ms. This scatter was overwhelmingly determined (ρ = −0.975, P < 0.001) by Information Content, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {\frac{\text{Signal}}{{{\text{Signal}} + {\text{Noise}}}}} $$\end{document}, an expression of signal-to-noise ratio. Averaging multiple replicates improves information content. In real clinical data, at resting, heart rate information content is often only 0.2–0.3; elevated pacing rates can raise information content above 0.5. Low information content (e.g. <0.5) causes gross overestimation of optimization-induced increment in VTI, high false-positive appearance of change in optimum between visits and very wide confidence intervals of individual patient optimum. AV and VV optimization by selecting the setting showing maximum cardiac function can only be accurate if information content is high. Simple steps to reduce noise such as averaging multiple replicates, or to increase signal such as increasing heart rate, can improve information content, and therefore viability, of any optimization process.
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