Continuous QT interval monitoring using insertable cardiac monitors during antiarrhythmic loading hospitalization: Results from the "LINQ QT" Study
Authors: Chu A F , Sagi V , Amin A K , Rajagopal G , Shantanu S , Pederson K S , Lautenbach A A 
Published: May 2024

Background

QT interval prolongation is associated with the development of potentially lethal cardiac arrhythmias. An implantable cardiac monitor (ICM) capable of longitudinal QT monitoring may allow for mobile assessment of dynamic changes in QT and assist in predicting long term cardiotoxicity.

Objective

Determine feasibility of continuous QTc interval monitoring in patients with ICM hospitalized for antiarrhythmic drug loading.

Methods

The previously described QT detection algorithm for an ICM determines the QT interval for every beat thus providing continuous long-term QT trends. QT intervals detected from continuously collected ICM ECG data from patients enrolled in a prospective clinical study from three sites was analyzed with the primary objective of studying the long-term QT interval trends in patients undergoing antiarrhythmic drug loading in an inpatient setting. The ICM ECG was processed through the QT detection algorithm which calculates the QTc interval for every beat to generate continuous long term QTc trends. Metrics including mean and median QTc, minimum and maximum QTc, and magnitude of QTc change were studied during the hospitalization period. Continuous QTc interval trend is presented from a patient displaying increase in QTc interval following antiarrhythmic drug loading during the hospitalization period.

Results

5 out of 17 patients enrolled (avg. age 71±7.3 years, 40% females) in the QT clinical study had continuous telemetered ICM ECG data available during the index antiarrhythmic loading hospitalization period. All patients were loaded with Sotalol during the hospitalization. All 5 patients had hypertension and atrial fibrillation (AF). 3 patients (60%) had a history of myocardial infarction (MI), congestive heart failure (CHF), and coronary artery disease (CAD) while 1 patient (20%) had diabetes. The magnitude of change in QTc over the hospitalization period was 139±42 msec with over 100 msec QTc change noticed in 4 of 5 patients (80%) (figure 1). Figure 2 shows continuous QTc interval trend observed from a patient (Male; Age:75; history of AF, hypertension, CHF, stroke) from this study showing a continuous increase in QTc interval. Overall, there was over 150 msec change in QTc observed for this patient during the hospitalization period. Premature ventricular complexes (PVCs) in a pattern of bigeminy were observed from ICM ECG for a 3-hr period from 12 pm-3 pm following the second antiarrhythmic dose which coupled with QT prolongation could indicate early signs of cardiotoxicity (figure 2). The five static 12-lead ECG measurements taken for this patient during the hospitalization period is also reported with the difference between these 12-lead QTc measurements and algorithm measured QTc being 22±8 msec.

Conclusion

ICM QT monitoring performed utilizing a QT interval detection algorithm can provide longitudinal and long-term dynamic QT trends in patients implanted with ICM.