Why the study?
Do Poincaré plots and power spectral analysis of short-term sinus cycle variations differentiate patients with sinus node dysfunction from normal controls?
Do Poincaré plots and power spectral analysis of short-term sinus cycle variations differentiate patients with sinus node dysfunction from normal controls?
Sinus node dysfunction is characterized by a loss of the inverse power law relationship in heart rate variability, which may serve as a novel diagnostic approach.
Answers are grounded in this paper and cite their sources.
May support Poincaré plots for differentiating sinus node dysfunction; hypothesis-generating pending prospective validation.
A salient feature of the normal sinus node activity is its prominent beat-to-beat variability, which shows self-similarity on different time scales (fractal dynamics). However, in patients with sinus node dysfunction, short-term time sinus cycles show exaggerated variability, the characteristics of which have not been analyzed. Therefore, Poincaré plots and power spectral analysis were applied to short-term variations of sinus cycles in 30 patients with and 30 patients without sinus node disease. Three patterns of behavior were observed in sick sinus patients: type 1, completely normal (n = 3); type 2, randomlike pattern in the Poincaré plots with "white noise" power spectra (n = 9); and type 3, a transitional pattern, characterized by remnants of normal behavior mixed with scattered points (n = 18). In control subjects, only type 1 (n = 27) and type 3 (n = 3) patterns were observed, P < 0.0001. The power spectral changes in sinus node dysfunction are thus characterized by a loss of the inverse power law relationship, which both has implications for heart rate variability analysis and might offer a new diagnostic approach.
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Bergfeldt et al. (2003) studied this question.
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