Susceptibility to Paroxysmal Atrial Fibrillation: A Study using Sinus Rhythm P Wave Parameters

International audienceEarly recognition of patients at high risk for atrial fibrillation may help to minimize potential health risks. The detection of susceptibility to develop atrial fibrillation is thus a real clinical challenge. Whereas many studies have used the signal-averaged P wave, the aim of this work is to determine whether electrocardiographic parameters resulting from the analysis of the P wave in ECG recorded during sinus rhythm could be markers for paroxysmal atrial fibrillation susceptibility. Our idea was to compare the ECG in sinus rhythm from two populations: healthy people and patients subject to paroxysmal atrial fibrillation. In addition to standard P wave parameters (P width, P-R interval,...), the Euclidean distance between beat-to-beat P waves, which has been rarely addressed in this context, was studied on lead V1. Significant differences between the healthy and the paroxysmal atrial fibrillation groups were obtained for various parameters. Moreover, a classification of the two groups based on the joint analysis of P width and P-R interval was suggested. This proposed classification could lead to an effective identification of patients at risk to develop atrial fibrillation

Digital DC-Reconstruction of AC-Coupled Electrophysiological Signals with a Single Inverting Filter

Since the introduction of digital electrocardiographs, high-pass filters have been necessary for successful analog-to-digital conversion with a reasonable amplitude resolution. On the other hand, such high-pass filters may distort the diagnostically significant ST-segment of the ECG, which can result in a misleading diagnosis. We present an inverting filter that successfully undoes the effects of a 0.05 Hz single pole high-pass filter. The inverting filter has been tested on more than 1600 clinical ECGs with one-minute durations and produces a negligible mean RMS-error of 3.1*10(-8) LSB. Alternative, less strong inverting filters have also been tested, as have different applications of the filters with respect to rounding of the signals after filtering. A design scheme for the alternative inverting filters has been suggested, based on the maximum strength of the filter. With the use of the suggested filters, it is possible to recover the original DC-coupled ECGs from AC-coupled ECGs, at least when a 0.05 Hz first order digital single pole high-pass filter is used for the AC-coupling

Comparison of automated interval measurements by widely used algorithms in digital electrocardiographs

Background: Automated measurements of electrocardiographic (ECG) intervals by current-generation digital electrocardiographs are critical to computer-based ECG diagnostic statements, to serial comparison of ECGs, and to epidemiological studies of ECG findings in populations. A previous study demonstrated generally small but often significant systematic differences among 4 algorithms widely used for automated ECG in the United States and that measurement differences could be related to the degree of abnormality of the underlying tracing. Since that publication, some algorithms have been adjusted, whereas other large manufacturers of automated ECGs have asked to participate in an extension of this comparison. Methods: Seven widely used automated algorithms for computer-based interpretation participated in this blinded study of 800 digitized ECGs provided by the Cardiac Safety Research Consortium. All tracings were different from the study of 4 algorithms reported in 2014, and the selected population was heavily weighted toward groups with known effects on the QT interval: included were 200 normal subjects, 200 normal subjects receiving moxifloxacin as part of an active control arm of thorough QT studies, 200 subjects with genetically proved long QT syndrome type 1 (LQT1), and 200 subjects with genetically proved long QT syndrome Type 2 (LQT2). Results: For the entire population of 800 subjects, pairwise differences between algorithms for each mean interval value were clinically small, even where statistically significant, ranging from 0.2 to 3.6 milliseconds for the PR interval, 0.1 to 8.1 milliseconds for QRS duration, and 0.1 to 9.3 milliseconds for QT interval. The mean value of all paired differences among algorithms was higher in the long QT groups than in normals for both QRS duration and QT intervals. Differences in mean QRS duration ranged from 0.2 to 13.3 milliseconds in the LQT1 subjects and from 0.2 to 11.0 milliseconds in the LQT2 subjects. Differences in measured QT duration (not corrected for heart rate) ranged from 0.2 to 10.5 milliseconds in the LQT1 subjects and from 0.9 to 12.8 milliseconds in the LQT2 subjects. Conclusions: Among current-generation computer-based electrocardiographs, clinically small but statistically significant differences exist between ECG interval measurements by individual algorithms. Measurement differences between algorithms for QRS duration and for QT interval are larger in long QT interval subjects than in normal subjects. Comparisons of population study norms should be aware of small systematic differences in interval measurements due to different algorithm methodologies, within-individual interval measurement comparisons should use comparable methods, and further attempts to harmonize interval measurement methodologies are warranted

Improving automatic analysis of the electrocardiogram acquired during magnetic resonance imaging using magnetic field gradient artefact suppression.

International audienceThe electrocardiogram (ECG) used for patient monitoring during magnetic resonance imaging (MRI) unfortunately suffers from severe artefacts. These artefacts are due to the special environment of the MRI. Modeling helped in finding solutions for the suppression of these artefacts superimposed on the ECG signal. After we validated the linear and time invariant model for the magnetic field gradient artefact generation, we applied offline and online filters for their suppression. Wiener filtering (offline) helped in generating reference annotations of the ECG beats. In online filtering, the least-mean-square filter suppressed the magnetic field gradient artefacts before the acquired ECG signal was input to the arrhythmia algorithm. Comparing the results of two runs (one run using online filtering and one run without) to our reference annotations, we found an eminent improvement in the arrhythmia module's performance, enabling reliable patient monitoring and MRI synchronization based on the ECG signal

Training process of the stepwise cluster analysis: influence of the number of clusters.

<p>The values of Se, PPV, Mean(Se,PPV) are reported at the optimal iteration step (3, 6, 9 clusters are assigned with the same marks as in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140123#pone.0140123.g004" target="_blank">Fig 4</a>). The best performing solution is defined for 9 clusters (Step 30). The continuous performance graphs are depicted by spline interpolation between the solutions at integer number of clusters.</p

Statistical distribution of the basic features for SVB and VB-class evaluated for the beats in the training dataset that are supplied to the input of Stage 2.

<p>Note:*All heartbeats that matched the reference template are assigned to SVB-class by Stage1.</p><p>The discrete features (F1-F5) are reported as frequency of observation; the continuous features (F6-F20) are represented as Mean±Std. The top-10 ranked second-order feature interactions selected by Cluster, Fuzzy, LDA, CT models are denoted in the row of each involved feature, specifying the index of the coupling feature in the interaction. If one feature is involved in several interactions, then the order of their selection in the model is used to list the respective coupling features.</p