Key result
Automatic STV algorithm shows ~0.80 correlation with gold standard fiducial segment averaging, reflecting pacing-induced changes.
Why the study?
Short-term variability of repolarization shows promise for real-time arrhythmic risk monitoring, prompting comparison of a novel automatic intracardiac electrogram measurement method against the gold standard in humans.
Does an automatic STV measurement algorithm accurately measure short-term variability of repolarization compared to the gold standard in patients with dual-chamber ICDs?
Observational (n=14)
Does an automatic STV measurement algorithm accurately measure short-term variability of repolarization compared to the gold standard in patients with dual-chamber ICDs?
Effect estimate: r = 0.80
p-value: p=<.0001
An automatic algorithm for measuring short-term variability of repolarization on intracardiac electrograms correlates strongly with the gold standard, enabling potential integration into ICDs for real-time arrhythmic risk monitoring.
May enable automated short-term variability assessment in ICD patients; leaves open arrhythmic risk prediction utility.
Background Short-term variability of repolarization (STV) increases prior to ventricular arrhythmias in both humans and animal models, making it a promising tool for real-time arrhythmic risk monitoring. Objective An automatic STV measurement algorithm was developed for intracardiac electrograms (EGMs) to enable integration into cardiac devices. This method previously demonstrated high accuracy in predicting life-threatening ventricular arrhythmias in animals. This study compared the performance of the automatic method to the gold standard on EGMs in humans. Methods EGM signals were recorded in 14 patients with a dual-chamber implantable cardioverter-defibrillator during de novo implantation (n = 5) or replacement (n = 9) procedures. Recordings were obtained in sinus rhythm (SR), atrial pacing at 80 beats/min, and dual-chamber pacing at 80 beats/min. STV was determined on the EGM from the activation recovery interval with the automatic method (STV-ARIauto) and with fiducial segment averaging (STV-ARIFSA), the gold standard. STV-ARIauto was compared with STV-ARIFSA for all pacing modes. Results STV-ARIauto and STV-ARIFSA decreased from 0.90 ± 0.51 ms and 0.99 ± 0.39 ms in SR (53 ± 9 beats/min) to 0.60 ± 0.37 ms (and 0.68 ± 0.39 ms in atrial pacing at 80 beats/min, and to 0.32 ± 0.15 ms and 0.59 ± 0.24 ms in dual-chamber pacing at 80 beats/min, respectively (all P < .05 compared with SR). STV-ARIauto strongly correlated with STV-ARIFSA (r = 0.80, P < .0001), with a small bias of 0.18 ms and limits of agreement between –0.35 and 0.70 ms. Conclusion The novel automatic STV measurement method accurately reflects pacing-induced changes, comparable to the gold standard. Future integration of this technique in implantable cardioverter-defibrillators could furnish continuous monitoring of arrhythmic risk and initiate preventive strategies.
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Chiu et al. (2025) conducted an observational in Patients with a dual-chamber implantable cardioverter-defibrillator (n=14). Automatic STV measurement algorithm (STV-ARIauto) vs. Fiducial segment averaging (STV-ARIFSA) was evaluated on Correlation and agreement between STV-ARIauto and STV-ARIFSA (r = 0.80, p=<.0001). An automatic short-term variability measurement algorithm strongly correlated with the gold standard fiducial segment averaging (r = 0.80, P < .0001) and accurately reflected pacing-induced changes.
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