Validation of automatic measurement of QT interval variability

Background Increased variability of beat-to-beat QT-interval durations on the electrocardiogram (ECG) has been associated with increased risk for fatal and non-fatal cardiac events. However, techniques for the measurement of QT variability (QTV) have not been validated since a gold standard is not available. In this study, we propose a validation method and illustrate its use for the validation of two automatic QTV measurement techniques. Methods Our method generates artificial standard 12-lead ECGs based on the averaged P-QRS-T complexes from a variety of existing ECG signals, with simulated intrinsic (QT interval) and extrinsic (noise, baseline wander, signal length) variations. We quantified QTV by a commonly used measure, short-term QT variability (STV). Using 28,800 simulated ECGs, we assessed the performance of a conventional QTV measurement algorithm, resembling a manual QTV measurement approach, and a more advanced algorithm based on fiducial segment averaging (FSA). Results The results for the conventional algorithm show considerable median absolute differences between the simulated and estimated STV. For the highest noise level, median differences were 4±6 ms in the absence of QTV. Increasing signal length generally yields more accurate STV estimates, but the difference in performance between 30 or 60 beats is small. The FSA algorithm proved to be very accurate, with most median absolute differences less than 0.5 ms, even for the highest levels of disturbance. Conclusions Artificially constructed ECGs with a variety of disturbances allow validation of QTV measurement procedures. The FSA algorithm provides highly accurate STV estimates under varying signal conditions, and performs much better than traditional beat-by-beat analysis. The fully automatic operation of the FSA algorithm enables STV measurement in large sets of ECGs

Short-Term Variability of the QT Interval Can be Used for the Prediction of Imminent Ventricular Arrhythmias in Patients With Primary Prophylactic Implantable Cardioverter Defibrillators

Background Short-term variability of the QT interval (STVQT) has been proposed as a novel electrophysiological marker for the prediction of imminent ventricular arrhythmias in animal models. Our aim is to study whether STVQT can predict imminent ventricular arrhythmias in patients. Methods and Results In 2331 patients with primary prophylactic implantable cardioverter defibrillators, 24-hour ECG Holter recordings were obtained as part of the EU-CERT-ICD (European Comparative Effectiveness Research to Assess the Use of Primary Prophylactic Implantable Cardioverter Defibrillators) study. ECG Holter recordings showing ventricular arrhythmias of >4 consecutive complexes were selected for the arrhythmic groups (n=170), whereas a control group was randomly selected from the remaining Holter recordings (n=37). STVQT was determined from 31 beats with fiducial segment averaging and calculated as [Formula: see text], where Dn represents the QT interval. STVQT was determined before the ventricular arrhythmia or 8:00 am in the control group and between 1:30 and 4:30 am as baseline. STVQT at baseline was 0.84±0.47 ms and increased to 1.18±0.74 ms (P<0.05) before the ventricular arrhythmia, whereas the STVQT in the control group remained unchanged. The arrhythmic patients were divided into three groups based on the severity of the arrhythmia: (1) nonsustained ventricular arrhythmia (n=32), (2) nonsustained ventricular tachycardia (n=134), (3) sustained ventricular tachycardia (n=4). STVQT increased before nonsustained ve

Example of simulated extrinsic disturbances.

<p>Top panel: artificial ECG signal constructed by concatenating the averaged P-QRS-T complex of the original ECG. Middle panel: artificial signal with added noise (SNR 20). Bottom panel: artificial signal with added residual baseline wander (standard deviation of slope 30 μV/s).</p

Median (95th percentile) of the absolute differences between the simulated STV and STV as measured by the FSA algorithm for different signal-to-noise ratios (SNR), residual baseline wander, and number of beats.

<p>Median (95th percentile) of the absolute differences between the simulated STV and STV as measured by the FSA algorithm for different signal-to-noise ratios (SNR), residual baseline wander, and number of beats.</p

Median (95th percentile) of the absolute differences between simulated STV and STV as measured by the MEANS algorithm for different signal-to-noise ratios (SNR), residual baseline wander, and number of beats.

<p>Median (95th percentile) of the absolute differences between simulated STV and STV as measured by the MEANS algorithm for different signal-to-noise ratios (SNR), residual baseline wander, and number of beats.</p

Example of a simulated QT-interval change.

<p>The black line indicates the original ECG signal with the vertical line denoting the end of the T wave as determined by the MEANS program. The grey line indicates the signal with a shifted end of the T wave. The horizontal bars below the signals mark symmetric windows of 180 ms around the end of the T wave in which the signal is not deformed. The signal segment from QRS end till the start of the window is extended, whereas the signal segment from the end of the window till the onset of the next P wave is compressed.</p

Circadian pattern of STV-QT in AS subgroups.

<p>Mean ± SEM at beginning of every hour in low AS (blue line, n = 15) and patients with high AS (red line, n = 15). * p < 0.05 compared to 0:00; § p <0.05 compared to low AS. STV-QT peaks at 08:00 and 18:00 in high AS patients, but is stable during the day in low AS patients.</p

Circadian pattern of RR- and QT-interval.

<p><b>(</b>A) mean ± SEM at beginning of every hour of total cohort (n = 30). Significant higher values are seen at night compared to during the day. * = p< 0.05 compared to 0:00. (B) Mean ± SEM at beginning of every hour of low AS-group (blue line, n = 15) and high AS group (red line, n = 15). No significant differences are found in the circadian pattern of RR-interval or QT-interval between low and high AS group.</p

Arrhythmia score (AS).

<p>Arrhythmia score (AS).</p