Continuous Monitoring of Cardiac Rhythms in Left Ventricular Assist Device Patients. Issue 3 (1st August 2013)

• Record Type: Journal Article
• Authors: Moscato, Francesco; Granegger, Marcus; Edelmayer, Michael; Zimpfer, Daniel; Schima, Heinrich
• Is Part Of: Artificial organs. Volume 38:Issue 3(2014:Mar.)
• Page Start: 191
• Page End: 198
• Publication Date: 2013-08-01
• Subjects: Artificial organs -- Periodicals; 617.956
• DOI: 10.1111/aor.12141
• Languages: English
• ISSNs: 0160-564X

Abstract

<abstract abstract-type="main"> <title>Abstract</title> <p>Monitoring of cardiac rhythms is of major importance in the treatment of heart failure patients with left ventricular assist devices (LVADs) implanted. A continuous surveillance of these rhythms could improve out‐of‐hospital care in these patients. The aim of this study was to investigate cardiac rhythms using available pump data only. Datasets (<italic>n</italic> = 141) obtained in the normal ward, in the intensive care unit, and during bicycle ergometry were analyzed in 11 recipients of a continuous flow LVAD (59.1 ± 9.7 years; male 82%). Tachograms and arrhythmic patterns derived from the pump flow waveform, and a simultaneously recorded ECG were compared, as well as heart rate variability parameters such as: the average heart beat duration (RR interval), the standard deviation of the beat duration (SDNN), the root‐mean‐square of the difference of successive beat durations (RMSSD), and the number of pairs of adjacent beat duration differing by >50 ms divided by the number of all beats (pNN50). A very good agreement of cardiac rhythm parameters from the pump flow compared with ECG was found. Tachycardia, atrial fibrillation, and extrasystoles could be accurately identified from the tachograms derived from the pump flow. Also, Bland–Altman analysis comparing pump flow with ECG indicated a very small difference in average RR interval of 0.3 ± 1.0 ms, in SSDN of 0.5 ± 2.7 ms, in RMSSD of 1.0 ± 5.6 ms, and in pNN50 of 0.3 ± 1.0%. Continuous monitoring of cardiac rhythms from available pump data is possible. It has the potential to reduce the out‐of‐hospital diagnostic burden and to permit a more efficient adjustment of the level of mechanical support.</p> </abstract>