Long-term QT interval analysis for real world patients with Insertable cardiac monitors taking antiarrhythmic drugs

Abstract

Abstract Background The QT interval serves as a surrogate biomarker for ventricular repolarization. Variance in QT intervals can clinically lead to pro-arrhythmia and sudden cardiac death. An insertable cardiac monitor (ICM) device capable of continuously monitoring the QT interval over a long period can provide diagnostic value for evaluating physiologic or drug induced variations in QT interval. Objective To analyze feasibility of continuous QTc interval monitoring in patients with ICM and evaluate the QTc interval changes in patients taking antiarrhythmic drugs. Methods Patients QT intervals detected from daily ICM ECG data from real-world patients taking antiarrhythmic drugs such as sotalol, amiodarone and dofetilide during hospitalization while implanted with ICM were analyzed from the de-identified Electronic Health Record (EHR) database linked with ICM device data warehouse. The ICM ECG was processed through the previously defined QT detection algorithm which calculates the QTc interval for every beat to generate continuous long term QTc trends. A patient contributed to the prescription group if they were prescribed antiarrhythmics drugs prior to hospitalization in the EHR database otherwise they contributed to the non-prescription group. Patients from the prescription group who were administered antiarrhythmic drugs via injection or IV during hospitalization were removed from the analysis. A 30-day median QTc interval from 30-60 days prior to hospitalization was used as baseline. Wilcoxon signed-rank test was used to compare the paired difference from days 1-5, 1-10, 30-60, and 60-90 after hospitalization to their respective baseline. Results 441 patients (avg. age: 70±11, 50.5% female) were included with 220 prescription and 221 non-prescription. The baseline QTc intervals were 414 and 417.3 msec for non-prescription and prescription groups, respectively. There was a significant increase in QTc on days 1-5, 1-10, 30-60, and 60-90 after hospital admission compared to the baseline (all p < 0.001) for the non-prescription group. The prescription group showed increase in QTc only on days 30-60 after hospitalization when compared to baseline (p<0.05). A larger QTc increase was observed in non-prescription receiving anti-arrhythmic loading on days 1-5 after hospitalization compared to patients on prescription prior to hospitalization (P<0.05). Conclusion Utilizing a QT interval detection algorithm from an ICM can provide long term QT trends for patients with an ICM. Continuous monitoring of QT can help to detect sudden changes in QT due to antiarrhythmic drugs which may lead to increased risk of arrhythmias or cardiac arrest.