The missing link: Unlocking the power of cardiac rhythm monitoring device based QT interval detection.

BACKGROUND: The QT interval is of high clinical value as QT prolongation can lead to Torsades de Pointes (TdP) and sudden cardiac death. Insertable cardiac monitors (ICMs) have the capability of detecting both absolute and relative changes in QT interval. In order to determine feasibility for long-term ICM based QT detection, we developed and validated an algorithm for continuous long-term QT monitoring in patients with ICM. METHODS: The QT detection algorithm, intended for use in ICMs, is designed to detect T-waves and determine the beat-to-beat QT and QTc intervals. The algorithm was developed and validated using real-world ICM data. The performance of the algorithm was evaluated by comparing the algorithm detected QT interval with the manually annotated QT interval using Pearson's correlation coefficient and Bland Altman plot. RESULTS: The QT detection algorithm was developed using 144 ICM ECG episodes from 46 patients and obtained a Pearson's coefficient of 0.89. The validation data set consisted of 136 ICM recorded ECG segments from 76 patients with unexplained syncope and 104 ICM recorded nightly ECG segments from 10 patients with diabetes and Long QT syndrome. The QT estimated by the algorithm was highly correlated with the truth data with a Pearson's coefficient of 0.93 (p < .001), with the mean difference between annotated and algorithm computed QT intervals of -7 ms. CONCLUSIONS: Long-term monitoring of QT intervals using ICM is feasible. Proof of concept development and validation of an ICM QT algorithm reveals a high degree of accuracy between algorithm and manually derived QT intervals.

Premature ventricular contraction detection for long-term monitoring in an implantable cardiac monitor.

BACKGROUND: Premature ventricular complexes (PVCs) are an important therapeutic target in symptomatic patients and in the setting of PVC-induced cardiomyopathy; however, measuring burden and therapeutic response is challenging. We developed and validated an algorithm for continuous long-term monitoring of PVC burden in an insertable cardiac monitor (ICM). METHODS: A high-specificity PVC detection algorithm was developed using real-world ICM data and validated using simultaneous Holter data and real-world ICM data. The PVC algorithm uses long-short-long RR interval sequence and morphology characteristics for three consecutive beats to detect the occurrence of single PVC beats. Data are expressed as gross incidence, patient average, and generalized estimating equation estimates, which were used to determine sensitivity, specificity, positive and negative predictive value (PPV, NPV). RESULTS: The PVC detection algorithm was developed on eighty-seven 2-min EGM strips recorded by an ICM to obtain a sensitivity and specificity of 75.9% and 98.8%. The ICM validation data cohort consisted of 787 ICM recorded ECG strips 7-16 min in duration from 134 patients, in which the algorithm detected PVC beats with a sensitivity, specificity, PPV, and NPV of 75.2%, 99.6%, 75.9%, and 99.5%, respectively. In the Holter validation dataset with continuous 2-h snippets from 20 patients, the algorithm sensitivity, specificity, PPV, and NPV were 74.4%, 99.6%, 68.8%, and 99.7%, respectively, for detecting PVC beats. CONCLUSIONS: The PVC detection algorithm was able to achieve a high specificity with only 0.4% of the normal events being incorrectly identified as PVCs, while detecting around three of four PVCs on a continuous long-term basis in ICMs.

Undetectable gadolinium brain retention in individuals with an age-dependent blood-brain barrier breakdown in the hippocampus and mild cognitive impairment.

INTRODUCTION: Blood-brain barrier (BBB) breakdown is an early independent biomarker of human cognitive dysfunction, as found using gadolinium (Gd) as a contrast agent. Whether Gd accumulates in brains of individuals with an age-dependent BBB breakdown and/or mild cognitive impairment remains unclear. METHODS: We analyzed T1-weighted magnetic resonance imaging (MRI) scans from 52 older participants with BBB breakdown in the hippocampus 19-28 months after either cyclic or linear Gd agent. RESULTS: There was no change in T1-weighted signal intensity between the baseline contrast MRI and unenhanced MRI on re-examination in any of the studied 10 brain regions with either Gd agent suggesting undetectable Gd brain retention. DISCUSSION: Gd does not accumulate in brains of older individuals with a BBB breakdown in the hippocampus. Thus, Gd agents can be used without risk of brain retention within a ∼2-year follow-up to study BBB in the aging human brain in relation to cognition and/or other pathologies.