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Published on: June 5, 2019
Ischemic risk stratification by means of multivariate analysis of the heart rate variability
José F Valencia1, Montserrat Vallverdú, Alberto Porta
1Department of Automatic Control, Centre for Biomedical Engineering Research, Universitat Politècnica de Catalunya, Barcelona, Spain. jose.fernando.valencia@upc.edu
Insights
Heart rate variability (HRV) complexity measures, combined with clinical factors, effectively stratify patients with ischemic dilated cardiomyopathy into cardiac risk groups, improving risk prediction.
Area of Science:
- Cardiology
- Biomedical Engineering
- Data Science
Background:
- Ischemic dilated cardiomyopathy (IDC) poses significant risks, necessitating accurate cardiac risk stratification.
- Heart rate variability (HRV) analysis offers insights into autonomic function and cardiac health.
- Current risk stratification methods may benefit from advanced HRV complexity measures.
Purpose of the Study:
- To stratify patients with IDC into cardiac risk groups using univariate and multivariate statistical analysis of HRV indexes.
- To evaluate the diagnostic performance of various HRV complexity measures and clinical parameters for predicting cardiac events.
- To determine the optimal combination of HRV indexes and clinical factors for enhanced risk classification.
Main Methods:
- RR interval series from IDC patients were analyzed using conditional entropy, refined multiscale entropy (RMSE), detrended fluctuation analysis, and time/frequency domain analysis.
- Univariate and multivariate linear discriminant analysis were employed for patient risk group classification.
- Sensitivity and specificity were calculated to assess the performance of HRV indexes and clinical parameters, considering two endpoints: sudden cardiac death and overall cardiac mortality over three years.
Main Results:
- A combination of one clinical parameter and one RMSE index achieved 80.0% sensitivity and 72.9% specificity during daytime.
- During nighttime, combining one clinical factor and two RMSE indexes yielded 80% sensitivity and 73.4% specificity.
- Longer time scales in RMSE were more relevant for nighttime risk classification, while shorter scales were better for daytime classification.
Conclusions:
- Left atrial size indexed to body surface and RMSE indexes are key for enhanced classification of IDC patients into risk groups.
- A single measurement is insufficient for comprehensive ischemic risk characterization.
- HRV complexity measures hold significant clinical relevance for improving risk stratification in IDC patients.
Abstract:
In this work, a univariate and multivariate statistical analysis of indexes derived from heart rate variability (HRV) was conducted to stratify patients with ischemic dilated cardiomyopathy (IDC) in cardiac risk groups. Indexes conditional entropy, refined multiscale entropy (RMSE), detrended fluctuation analysis, time and frequency analysis, were applied to the RR interval series (beat-to-beat series), for single and multiscale complexity analysis of the HRV in IDC patients. Also, clinical parameters were considered. Two different end-points after a follow-up of three years were considered: (i) analysis A, with 151 survivor patients as a low risk group and 13 patients that suffered sudden cardiac death as a high risk group; (ii) analysis B, with 192 survivor patients as a low risk group and 30 patients that suffered cardiac mortality as a high risk group. A univariate and multivariate linear discriminant analysis was used as a statistical technique for classifying patients in risk groups. Sensitivity (Sen) and specificity (Spe) were calculated as diagnostic criteria in order to evaluate the performance of the indexes and their linear combinations. Sen and Spe values of 80.0% and 72.9%, respectively, were obtained during daytime by combining one clinical parameter and one index from RMSE, and during nighttime Sen = 80% and Spe = 73.4% were attained by combining one clinical factor and two indexes from RMSE. In particular, relatively long time scales were more relevant for classifying patients into risk groups during nighttime, while during daytime shorter scales performed better. The results suggest that the left atrial size, indexed to body surface and RMSE indexes are those that allow enhanced classification of ischemic patients in their respective risk groups, confirming that a single measurement is not enough to fully characterize ischemic risk patients and the clinical relevance of HRV complexity measures.
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