Literature DB >> 24671897

Trying to predict the unpredictable: Variations in device-based daily monitored diagnostic parameters can predict malignant arrhythmic events in patients undergoing cardiac resynchronization therapy.

Ewa Jędrzejczyk-Patej1, Oskar Kowalski, Beata Sredniawa, Patrycja Pruszkowska, Adam Sokal, Mariola Szulik, Michał Mazurek, Jacek Kowalczyk, Zbigniew Kalarus, Radosław Lenarczyk.   

Abstract

BACKGROUND: The aim of this study was to evaluate the value of device-based diagnostic parameters in predicting ventricular arrhythmias in cardiac resynchronization therapy (CRT) recipients.
METHODS: Ninety-six CRT-D patients participating in TRUST CRT Trial were analyzed. The inclusion criteria were: heart failure in NYHA ≥ 3 class, QRS ≥ 120 ms, LVEF £ 35% and significant mechanical dyssynchrony. Patients were divided into those with (n = 31, 92 arrhythmias) and without (n = 65) appropriate ICD interventions within follow-up of 12.03 ± 6.7 months. Daily monitored device-based parameters: heart rate (HR), thoracic impedance (TI), HR variability and physical activity were analyzed in 4 time windows: within 10, 7, 3 days and 1 day before appropriate ICD interventions.
RESULTS: A consistent pattern of changes in three monitored factors was observed prior to arrhythmia: 1) a gradual increase of day HR (from 103.43% of reference within 10-day window to 105.55% one day before, all p < 0.05 vs. reference); 2) variations in night HR (104.75% in 3 days, 107.65% one day before, all p < 0.05) and 3) TI decrease (from 97.8% in 10 days to 96.81% one day before, all p < 0.05). The combination of three parameters had better predictive value, which improved further after exclusion of patients with atrial fibrillation (AF). The predictive model combining HR and TI together with LVEF and NT-proBNP was more prognostic than the model involving LVEF and NT-proBNP alone (difference in AUC 0.05, 95% CI 0.0005-0.09, p = 0.04).
CONCLUSIONS: Daily device-monitored parameters show significant variations prior to ventricular arrhythmia. Combination of multiple parameters improves arrhythmia predictive performance by its additive value to baseline risk factors, while presence of AF diminishes it.

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Year:  2014        PMID: 24671897     DOI: 10.5603/CJ.a2014.0022

Source DB:  PubMed          Journal:  Cardiol J        ISSN: 1898-018X            Impact factor:   2.737


  1 in total

1.  Using Consumer-Wearable Activity Trackers for Risk Prediction of Life-Threatening Heart Arrhythmia in Patients with an Implantable Cardioverter-Defibrillator: An Exploratory Observational Study.

Authors:  Diana My Frodi; Vlad Manea; Søren Zöga Diederichsen; Jesper Hastrup Svendsen; Katarzyna Wac; Tariq Osman Andersen
Journal:  J Pers Med       Date:  2022-06-08
  1 in total

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