Related Experiment Videos
Structural relationships between measures based on heart beat intervals: potential for improved risk assessment
Alfred P Hallstrom1, Phyllis K Stein, Raphael Schneider
1Department of Biostatistics, University of Washington, Seattle, WA 98105-4689, USA. aph@u.washington.edu
IEEE Transactions on Bio-Medical Engineering
|August 18, 2004
Summary
Adjusting electrocardiogram (ECG) measures for heart rate and ventricular premature contractions improves risk stratification for lethal arrhythmias. Rescaling ECG data reduces variability and enhances predictive power for cardiac patients.
Area of Science:
- Cardiology
- Biomedical Engineering
- Medical Informatics
Background:
- Decreased left ventricular ejection fraction identifies high-risk patients for lethal ventricular arrhythmias.
- Current 24-hour ECG risk stratification methods include ventricular premature contraction (VPC) counts, heart rate variability (HRV), and heart rate turbulence (HRT).
- Refining these ECG measures can improve their clinical utility for risk stratification.
Purpose of the Study:
- To explore structural relationships between heart rate (HR), HRV, and HRT measures.
- To develop a method for separating the influence of average HR on HRV and HRT measures, potentially reducing variability and increasing risk stratification power.
- To propose an adjusted turbulence slope (TS) independent of VPC count and evaluate shorter ECG recordings for HRV and HRT estimation.
Main Methods:
- Re-scaled tachograms of heart-beat intervals to a standardized HR of 75 bpm (800 ms average interval).
- Calculated HRV and HRT measures from re-scaled time series and standard data.
- Explored relationships between VPC count and HRT, and proposed an adjusted TS.
- Evaluated measures using ambulatory ECG recordings from 744 patients in the Cardiac Arrhythmia Suppression Trial.
Main Results:
- Re-scaled HRV and HRT measures exhibited reduced variance (20%–40%) and substantially lower correlations between measures.
- Found circadian effects on some HRV indices not explained by HR patterns, suggesting potential for additional risk prediction measures.
- Demonstrated that TS is structurally related to VPC count, leading to the proposal of a VPC-independent adjusted TS.
Conclusions:
- Adjusting ambulatory ECG measures for HR and VPC count can significantly enhance their power for risk stratification in cardiac patients.
- Re-scaling tachograms offers a promising approach to reduce variability and improve the reliability of HRV and HRT measures.
- Further research into circadian effects and novel ECG markers may yield additional improvements in cardiac risk prediction.