Optimization of Cardiac Resynchronization Therapy: Echocardiographic vs Semiautomatic Device Algorithms

Inadvertent QRS prolongation by an optimization device-based algorithm in patients with cardiac resynchronization therapy

Background

Device-based algorithms offer the potential for automated optimization of cardiac resynchronization therapy (CRT), but the process for accepting them into clinical use is currently still ad-hoc, rather than based on pre-clinical and clinical testing of specific features of validity. We investigated how the QuickOpt-guided VV delay (VVD) programming performs against the clinical and engineering heuristic of QRS complex shortening by CRT.

Methods

A prospective, 2-center study enrolled 37 consecutive patients with CRT. QRS complex duration (QRSd) was assessed during intrinsic atrioventricular conduction, synchronous biventricular pacing, and biventricular pacing with QuickOpt-proposed VVD. The measurements were done manually by electronic calipers in signal-averaged and magnified 12-lead QRS complexes.

Results

Native QRSd was 174 ± 22 ms. Biventricular pacing with empiric AVD and synchronous VVD resulted in QRSd 156 ± 20 ms, a significant narrowing from the baseline QRSd by 17 ± 27 ms, P = 0.0003. In 36 of 37 patients, the QuickOpt algorithm recommended left ventricular preexcitation with VVD of 42 ± 18 ms (median 40 ms; interquartile range 30–55 ms, P <0.00001). QRSd in biventricular pacing with QuickOpt-based VVD was significantly longer compared with synchronous biventricular pacing (168 ± 25 ms vs. 156 ± 20 ms; difference 12 ± 11ms; P <0.00001). This prolongation correlated with the absolute VVD value (R = 0.66, P <0.00001).

Conclusions

QuickOpt algorithm systematically favours a left-preexcitation VVD which translates into a significant prolongation of the QRSd compared to synchronous biventricular pacing. There is no reason to believe that a manipulation that systematically widens QRSd should be considered to optimize physiology. Device-based CRT optimization algorithms should undergo systematic mechanistic pre-clinical evaluation in various scenarios before they are tested in large clinical studies.

Cardiac resynchronisation therapy optimisation strategies: systematic classification, detailed analysis, minimum standards and a roadmap for development and testing

In this article an international group of CRT specialists presents a comprehensive classification system for present and future schemes for optimising CRT. This system is neutral to the measurement technology used, but focuses on little-discussed quantitative physiological requirements. We then present a rational roadmap for reliable cost-effective development and evaluation of schemes. A widely recommended approach for AV optimisation is to visually select the ideal pattern of transmitral Doppler flow. Alternatively, one could measure a variable (such as Doppler velocity time integral) and "pick the highest". More complex would be to make measurements across a range of settings and "fit a curve". In this report we provide clinicians with a critical approach to address any recommendations presented to them, as they may be many, indistinct and conflicting. We present a neutral scientific analysis of each scheme, and equip the reader with simple tools for critical evaluation. Optimisation protocols should deliver: (a) singularity, with only one region of optimality rather than several; (b) blinded test-retest reproducibility; (c) plausibility; (d) concordance between independent methods; and (e) transparency, with all steps open to scrutiny. This simple information is still not available for many optimisation schemes. Clinicians developing the habit of asking about each property in turn will find it easier to win now down the broad range of protocols currently promoted. Expectation of a sophisticated enquiry from the clinical community will encourage optimisation protocol-designers to focus on testing early (and cheaply) the basic properties that are vital for any chance of long term efficacy.

Long-term clinical effects of programmer-guided atrioventricular and interventricular delay optimization: Intracardiac electrography versus echocardiography for cardiac resynchronization therapy in patients with heart failure

Objectives

To compare the haemodynamic results and long-term clinical outcomes of intracardiac electrography (QuickOpt®; St Jude Medical, St Paul, MN, USA) and echocardiography for optimization of atrioventricular (AV) and interventricular (VV) delays in cardiac resynchronization therapy (CRT).

Methods

Patients with CRT devices were prospectively enrolled; AV/VV delays were optimized by either QuickOpt® or echocardiography. Patients in the QuickOpt® group underwent both echocardiography and QuickOpt® optimization, and QuickOpt® AV/VV delays were used to program the CRT. All patients were followed-up for 12 months.

Results

In total, 44 patients were enrolled. There was good correlation between AV/VV delays determined by QuickOpt® ( n = 20) and echocardiography ( n = 24). QuickOpt® was significantly faster than echocardiography-guided optimization. Cardiac function, 6-min walking distance and left ventricular ejection fraction were significantly and similarly improved in both groups at 6 and 12 months compared with baseline. In the QuickOpt® group, left ventricular end diastolic diameters were significantly smaller at 6 and 12 months compared with baseline.

Conclusions

QuickOpt® is a quick, convenient and easy to perform method for optimization of AV and VV delays, with a similar long-term clinical outcome to echocardiography-guided optimization.

When is an optimization not an optimization? Evaluation of clinical implications of information content (signal-to-noise ratio) in optimization of cardiac resynchronization therapy, and how to measure and maximize it

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, [Formula: see text], 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.

Electrogram-based optimal atrioventricular and interventricular delays of cardiac resynchronization change individually during exercise

BACKGROUND

Limited data suggest that optimal atrioventricular (AV) and interventricular (VV) delays are different at rest than during exercise in patients with heart failure. We assessed the feasibility and reproducibility of an electrogram-based method of optimization called QuickOpt at rest and during exercise.

METHODS

Patients with a St Jude Medical cardiac resynchronization therapy implantable cardioverter-defibrillator were subjected to a graded treadmill test, and QuickOpt was repeatedly measured prior to, during, and after the exercise.

RESULTS

Twenty-four patients (16 males, aged 67.4 ± 7.7 years) participated. At rest, delays (in ms) were 110.4 ± 20.1 for sensed AV delay and -70 (LV pacing first) to +20 (RV pacing first) for VV delay. The changes in QuickOpt-derived delays at rest were not significant despite change in body position. During exercise, QuickOpt-derived AV delays did not change in 11 patients, were shorter during peak exercise in 8 patients, and were longer in 3 patients (average value during peak exercise was 126.5 ± 15.8 ms, P = 0.04 compared to baseline). The QuickOpt-derived VV delay gradually shifted toward earlier right ventricular pacing during exercise in 19 patients, while no changes were seen in 3 patients, and a shift occurred toward earlier left ventricular pacing in 2 patients (average value during peak exercise was -30.7 ± 22.2; P = 0.001 compared to baseline). There was no correlation between changes in the QuickOpt-derived AV and VV delays and heart rate.

CONCLUSIONS

The application of electrogram-based algorithm is feasible both at rest and during exercise. The results are reproducible. QuickOpt-derived AV and VV delays individually change during exercise.