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Endocardial acceleration (sonR) vs. ultrasound-derived time intervals in recipients of cardiac resynchronization therapy systems.
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Edité par CCSD ; Oxford University Press (OUP) -
International audience. AIMS: Optimization of cardiac resynchronization therapy (CRT) requires the gathering of cardiac functional information. An accurate timing of the phases of the cardiac cycle is key in the optimization process. METHODS AND RESULTS: We compared Doppler echocardiography to an automated system, based on the recording of sonR (formerly endocardial acceleration), in the detection of mitral and aortic valves closures and measurements of the duration of systole and diastole. We prospectively studied, under various conditions of cardiac stimulation, 75 recipients of CRT systems (69% men), whose mean age was 72 ± 9.2 years, left ventricular ejection fraction 35 ± 11%, baseline QRS duration 154 ± 29 ms, and New York Heart Association functional class 3.0 ± 0.7. We simultaneously recorded (i) sonR, detected by a non-invasive piezoelectric micro-accelerometer sensor clipped onto an electrode located in the parasternal region, (b) electrocardiogram, and (c) Doppler audio signals, using a multichannel data acquisition and analysis system. The correlation between timing of mitral and aortic valve closure by sonR vs. Doppler signals was examined by linear regression analysis. Correlation coefficients and the average absolute error were calculated. A concordance in the timing of the mitral (r = 0.86, error = 9.7 ms) and aortic (r = 0.93, error = 9.7 ms) valves closure was observed between the two methods in 94% of patients. Similarly, sonR and the Doppler-derived measurements of systolic (r = 0.85, error = 13.4 ms) and diastolic (r = 0.99, error = 12 ms) interval durations were concordant in 80% of patients. CONCLUSION: A high concordance was found between sonR and the cardiac ultrasound in the timings of aortic and mitral valve closures and in the estimation of systolic and diastolic intervals durations. These observations suggest that sonR could be used to monitor cardiac function and adaptively optimize CRT systems.
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