Rhythm analysis and charging during chest compressions reduces compression pause time.

PURPOSE: Prolonged chest compression interruptions immediately preceding and following a defibrillation shock reduce shock success and survival after cardiac arrest. We tested the hypothesis that compression pauses would be shorter using an AED equipped with a new Analysis during Compressions with Fast Reconfirmation (ADC-FR) technology, which features automated rhythm analysis and charging during compressions with brief reconfirmation analysis during compression pause, compared with standard AED mode. METHODS: BLS-certified emergency medical technicians (EMTs) worked in pairs and performed two trials of simulated cardiac resuscitation with a chest compression sensing X Series defibrillator (ZOLL Medical). Each pair was randomized to perform a trial of eight 2-min compression intervals (randomly assigned to receive four shockable and four non-shockable rhythms) with the defibrillator in standard AED mode and another trial in ADC-FR mode. Subjects were advised to follow defibrillator prompts, defibrillate if "shock advised," and switch compressors every two intervals. Compression quality data were reviewed using RescueNet Code Review (ZOLL Medical) and analyzed using paired t-tests. RESULTS: Thirty-two EMT-basic prehospital providers (59% male; median 25 years age [IQR 22-27]) participated in the study. End of interval compression interruptions were significantly reduced with ADC-FR vs. AED mode (p<0.001). For shockable rhythms, pre-shock pause was reduced significantly with ADC-FR compared with AED use (7.35±0.16s vs. 12.0±0.22s, p<0.001) whereas post-shock pause was similar (2.08±0.14s vs. 1.77±0.14s, p=0.1). CONCLUSION: Chest compression interruptions associated with rhythm analysis and charging are reduced with use of a novel defibrillator technology, ADC-FR, which features automated rhythm analysis and charging during compressions.

Critique of arrhythmia detectors based on heuristic rules.

Every arrhythmia detector employs a beat classifier to discriminate between normal (N) and ventricular (V) beats. In most of these beat-classification algorithms, a set of rules is employed to distinguish between N and V beats using a common set of features extracted from the real-time ECG signal and/or correlation of QRS complexes with the dominant QRS template. A common set of these features includes: beat area, beat width, beat amplitude, beat polarity, and R-to-R interval. Heuristic methods are commonly used to adapt the rules to particular databases. These classifiers are rule-based classifiers that employ AND-OR binary structures and hand-tuned thresholds for making decisions in the feature space. The complexity of the feature space increases as the number of features increases. For k features, a k-dimensional space is required. Thus, the separation between N and V space distributions becomes more difficult, especially since these distributions overlap. When AND-OR binary structures with hand-tuned thresholds or linear-separation techniques are used to separate N and V distributions in a k-dimensional feature space, errors are guaranteed, because these distributions are not linearly separable. As a results, these algorithms have limited dynamic ranges. This means that the sensitivity for a certain class of beats (N or V) will grow only at the expense of positive predictivity for that class, and vice versa.

Automated testing of arrhythmia monitors using annotated databases.

Arrhythmia-algorithm performance is typically tested using the AHA and MIT/BIH databases. The tools for this test are simulation software programs. While these simulations provide rapid results, they neglect hardware and software effects in the monitor. To provide a more accurate measure of performance in the actual monitor, a system has been developed for automated arrhythmia testing. The testing system incorporates an IBM-compatible personal computer, a digital-to-analog converter, an RS232 board, a patient-simulator interface to the monitor, and a multi-tasking software package for data conversion and communication with the monitor. This system "plays" patient data files into the monitor and saves beat classifications in detection files. Tests were performed using the MIT/BIH and AHA databases. Statistics were generated by comparing the detection files with the annotation files. These statistics were marginally different from those that resulted from the simulation. Differences were then examined. As expected, the differences were related to monitor hardware effects.

Three-dimensional myocardial and ventricular shape: a surface representation.

To date, a detailed three-dimensional (3D) analysis of cardiac shape and size has not been available. Accordingly, we developed a method for such an analysis using sectioned hearts and a computer-based 3D description of the epi- and endocardial surfaces of the left and right ventricles (LV and RV) and the interventricular septum. The accuracy of this analysis as a function of section thickness (hs) was evaluated and reference axes for the LV, RV, and myocardium determined in eight canine hearts. After diastolic arrest, the RV, LV, and their atria were fixed in formaldehyde solution at pressures of 6 and 12 cmH2O, respectively. The hearts were then cast (plastic or gelatin) and sectioned, and the surfaces were digitized. We found that 1) accurate 3D computer reconstructions and computed volumes of the LV, RV, and myocardium were obtained then hs less than or equal to 5 mm, 2) the apex-to-base circumference and cross-sectional area relations could be approximated provided hs less than 10 mm, and 3) the section centers of gravity for the LV, RV, and myocardium defined three distinct vertical lines. Thus, an accurate description of 3D configuration is obtainable by a 5-mm section thickness. The centers of gravity provide a set of geometrical references for the study of shape in normal and diseased hearts.