Changes in paced signals may predict in-hospital cardiac arrest
Mina Attin1, Spencer Z Rosero2, Jimmy Ding3
1School of Nursing, University of Rochester Medical Center, Rochester, NY, USA.
Insights
Predicting in-hospital cardiac arrest (I-HCA) in patients with pacemakers and implantable cardioverter-defibrillators (ICDs) may be possible by analyzing electrocardiogram (ECG) signals. Prolonged QRS duration and heart rate variability are key indicators preceding I-HCA events.
Area of Science:
- Cardiology
- Biomedical Engineering
- Medical Device Technology
Background:
- Increasing prevalence of cardiac rhythm management devices (pacemakers, ICDs) in patients with chronic illnesses.
- Need for predictive markers of in-hospital cardiac arrest (I-HCA) in patients with implanted cardiac devices.
Purpose of the Study:
- To identify electrocardiogram (ECG) predictors of in-hospital cardiac arrest (I-HCA) in cardiovascular patients with implanted cardiac rhythm devices.
- To analyze paced ECG signals for potential early warning signs of cardiac arrest.
Main Methods:
- Retrospective analysis of full-disclosure ECG traces from 17 subjects prior to documented I-HCA.
- Determination of R-R intervals and QRS durations (QRSd) from ECG signals.
- Comparison of ECG parameters in the hours preceding I-HCA and within minutes of arrest.
Main Results:
- Ventricular paced QRS duration prolongation observed in 63% of subjects prior to I-HCA.
- Significantly greater QRS duration immediately preceding cardiac arrest compared to 8 hours prior (P < 0.05).
- Heart rate variability and QRS duration differed significantly between arrest types (PEA/asystole vs. VT/VF).
Conclusions:
- Diagnostic ECG patterns from telemetry data can predict adverse events like I-HCA in patients with implanted devices.
- Detection of significant ECG changes may offer prognostic value for timely intervention.
- Further research can refine ECG analysis for early I-HCA detection and patient management.
Background:
An increasing number of patients with chronic illnesses have implanted cardiac rhythm devices such as pacemakers and implantable cardioverter-defibrillators (ICDs). This study was conducted to identify potentially useful predictors of in-hospital cardiac arrest (I-HCA) within paced electrocardiogram (ECG) signals from cardiovascular patients with implanted medical devices.
Methods:
In this retrospective study of 17 subjects, full-disclosure ECG traces prior to the time of documented I-HCA were analyzed to determine R-R intervals and QRS durations (QRSd).
Results:
Ventricular paced QRSd prolongation was observed prior to I-HCA in 10/16 (63%) subjects. QRSd was significantly greater immediately preceding cardiac arrest than during each of the 8 hours prior to cardiac arrest (P < 0.05). Heart rate changes (measured using standard deviation) within 15 minutes of cardiac arrest were significantly greater in subjects with pulseless electrical activity (PEA)/asystolic arrest compared to those with cardiac arrests due to ventricular tachycardia/ventricular fibrillation (VT/VF) (10.13 vs 3.31; P = 0.024). Significant differences over the 8 hours preceding cardiac arrest in heart rate (74 vs 86 beats/min; P = 0.002) and QRS duration (172 ms vs 137 ms; P < 0.001) were observed between subjects with initial rhythms of VT/VF and those with initial rhythms of PEA/asystole.
Conclusions:
Patterns of diagnostic ECG features can be extracted from the telemetry data of patients with implanted medical devices prior to adverse events including I-HCA. The detection of these significant changes might have an immediate prognostic impact on the timely treatment of some patients at risk of adverse events.
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