Lagged segmented Poincar plot analysis for risk stratification in patients with dilated cardiomyopathy
The objectives of this study were to introduce a new type of heart-rate variability analysis improving risk stratification in patients with idiopathic dilated cardiomyopathy (DCM) and to provide additional information about impaired heart beat generation in these patients. Beat-to-beat intervals (BBI) of 30-min ECGs recorded from 91 DCM patients and 21 healthy subjects were analyzed applying the lagged segmented Poincar plot analysis (LSPPA) method. LSPPA includes the Poincar plot reconstruction with lags of 1100, rotating the cloud of points, its normalized segmentation adapted to their standard deviations, and finally, a frequency-dependent clustering. The lags were combined into eight different clusters representing specific frequency bands within 0.0121.153Hz. Statistical differences between low- and high-risk DCM could be found within the clusters IIVIII (e.g., cluster IV: 0.0330.038Hz; p=0.0002; sensitivity=85.7%; specificity=71.4%). The multivariate statistics led to a sensitivity of 92.9%, specificity of 85.7% and an area under the curve of 92.1% discriminating these patient groups. We introduced the LSPPA method to investigate time correlations in BBI time series. We found that LSPPA contributes considerably to risk stratification in DCM and yields the highest discriminant power in the low and very low-frequency bands.
poincar plot risk stratification dilated cardiomyopathy heart-rate variability nonlinear dynamics