Detection of cardiac arrest using a simplified frequency analysis of the impedance cardiogram recorded from defibrillator pads.

An algorithm based only on the impedance cardiogram (ICG) recorded through two defibrillation pads, using the strongest frequency component and amplitude, incorporated into a defibrillator could determine circulatory arrest and reduce delays in starting cardiopulmonary resuscitation (CPR). Frequency analysis of the ICG signal is carried out by integer filters on a sample by sample basis. They are simpler, lighter and more versatile when compared to the FFT. This alternative approach, although less accurate, is preferred due to the limited processing capacity of devices that could compromise real time usability of the FFT. These two techniques were compared across a data set comprising 13 cases of cardiac arrest and 6 normal controls. The best filters were refined on this training set and an algorithm for the detection of cardiac arrest was trained on a wider data set. The algorithm was finally tested on a validation set. The ICG was recorded in 132 cardiac arrest patients (53 training, 79 validation) and 97 controls (47 training, 50 validation): the diagnostic algorithm indicated cardiac arrest with a sensitivity of 81.1% (77.6-84.3) and specificity of 97.1% (96.7-97.4) for the validation set (95% confidence intervals). Automated defibrillators with integrated ICG analysis have the potential to improve emergency care by lay persons enabling more rapid and appropriate initiation of CPR and when combined with ECG analysis they could improve on the detection of cardiac arrest.

An early phase of slow myocardial activation may be necessary in order to benefit from cardiac resynchronization therapy.

BACKGROUND: Not all patients with a QRS duration longer than 140 milliseconds respond to cardiac resynchronization therapy (CRT). The same QRS duration may correspond to different spatiotemporal patterns of myocardial activation that influence response to CRT. METHODS: Electrocardiographic imaging based on 80 chest wall electrodes was used to construct the spatiotemporal myocardial activation map in 46 consecutive patients before CRT. The cumulative percentage of myocardium activated was plotted against time expressed in terms of quintiles of the overall QRS duration. Changes in the left ventricular ejection fraction and end-diastolic diameter, maximum oxygen consumption per minute, brain natriuretic peptide level, and 6-minute walk distance after 6 months of CRT were compared across different patterns with 1-way analysis of variance. RESULTS: Data from 34 patients were available for analysis. Four spatiotemporal patterns of myocardial activation could be identified: triphasic (fast-slow-fast) (13), uniform (8), fast-slow (7), and slow-fast (6). The overall QRS duration was similar in the 4 groups (166 +/- 19 vs 138 +/- 21 vs 157 +/- 26 vs 152 +/- 37 milliseconds, P = not significant [NS]). The ejection fraction showed a trend of greater increases for the triphasic (6.5% +/- 7.0%) and slow-fast (15.5% +/- 6.4%) patterns than for the uniform (4.0% +/- 13.3%) and fast-slow (8.0% +/- 6.1%) patterns (P = NS). The end-diastolic diameter showed a trend of greater decreases for the triphasic (-3.7% +/- 5.3%) and slow-fast (-7.0% +/- 6.7%) patterns than for the uniform (0.8% +/- 6.7%) and fast-slow (0.0% +/- 4.6%) patterns (P = NS). The maximum oxygen consumption per minute showed a trend of greater increases for the triphasic (1.2 +/- 4.2 mL/kg/min) and slow-fast (4.1 +/- 2.7 mL/kg/min) patterns than for the uniform (0.1 +/- 4.1 mL/kg/min) and fast-slow (1.0 +/- 2.1 mL/kg/min) patterns (P = NS). The brain natriuretic peptide level decreased significantly more for the triphasic (-450 +/- 1269) and slow-fast (-3121 +/- 1512) patterns than for the uniform (762 +/- 1036) and fast-slow (718 +/- 2530) patterns (P = .0003). The 6-minute walk distance increased significantly more for the triphasic (29 +/- 89) and slow-fast (40 +/- 23) patterns than for the uniform (6 +/- 87) and fast-slow (37 +/- 45) patterns (P = .0003). CONCLUSIONS: Different spatiotemporal patterns of myocardial activation exist among patients with broad QRS complex and may affect response to CRT. An early phase of slow myocardial activation (the triphasic fast-slow-fast and the slow-fast patterns) may be necessary for a patient to benefit from CRT.

Activation patterns during selective pacing of the left ventricle can be characterized using noninvasive electrocardiographic imaging.

BACKGROUND: Noncontact endocardial mapping allows accurate beat-to-beat reconstruction of the reentrant pathway of ventricular tachycardia and improves outcomes after ablation. Several studies support electrocardiographic imaging (ECGI) as a means of noninvasively outlining epicardial activation despite constraints of internal geometry. However, few have explored its clinical application. This study aims to evaluate ECGI during selective left ventricular (LV) pacing, relative to an invasive approach. METHODS: Multisite pacing was performed within the left ventricles of 3 patients undergoing invasive procedures. Simultaneous recording of endocardial potentials using a noncontact multielectrode array and body surface potentials (BSP) using an 80-electrode torso vest was performed. A total of 16 recordings were made. The inverse solution was applied to BSP to reconstruct epicardial activation. Single-paced beats from real and virtual electrograms were used to construct 3-dimensional isochronal and isopotential maps. Endocardial and epicardial data were then superimposed onto a single geometry to allow quantitative comparison of activation foci. RESULTS: Good correlation was observed between endocardial activation patterns and those reconstructed from BSP using ECGI. This was repeatedly demonstrated in all LV regions except for the septum (3 recordings). Epicardial isochronal maps were able to locate early and late activation to mean distances of 13.8 +/- 4.7 and 12.5 +/- 3.7 mm from endocardial data. Isopotential maps localized pacing sites with comparable accuracy (14 +/- 5.3 mm). CONCLUSIONS: Body surface potentials and reconstructed epicardial activation patterns during LV pacing correlate well with endocardial data acquired invasively. The exception was during pacing of the septum. Although early results are encouraging, further quantitative data are required to fully validate and apply this noninvasive tool in the clinical arena.