| Title |
Heart rate variability and nonlinear dynamic analysis in patients with stress-induced cardiomyopathy
|
|---|---|
| Published in |
Medical & Biological Engineering & Computing, August 2012
|
| DOI | 10.1007/s11517-012-0947-z |
| Pubmed ID | |
| Authors |
Goran Krstacic, Gianfranco Parati, Dragan Gamberger, Paolo Castiglioni, Antonija Krstacic, Robert Steiner |
| Abstract |
Complexity-based analyses may quantify abnormalities in heart rate variability (HRV). The aim of this study was to investigate the clinical and prognostic significances of dynamic HRV changes in patients with stress-induced cardiomyopathy Takotsubo syndrome (TS) by means of linear and nonlinear analysis. Patients with TS were included in study after complete noninvasive and invasive cardiovascular diagnostic evaluation and compared to an age and gender matched control group of healthy subjects. Series of R-R interval and of ST-T interval values were obtained from 24-h ECG recordings after digital sampling. HRV analysis was performed by 'range rescaled analysis' to determine the Hurst exponent, by detrended fluctuation analysis to quantify fractal long-range correlation properties, and by approximate entropy to assess time-series predictability. Short- and long-term fractal-scaling exponents were significantly higher in patients with TS in acute phases, opposite to lower approximate entropy and Hurst exponent, but all variables normalized in a few weeks. Dynamic HRV analysis allows assessing changes in complexity features of HRV in TS patients during the acute stage, and to monitor recovery after treatment, thus complementing traditional ECG and clinically analysis. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| Unknown | 69 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 24% |
| Student > Master | 11 | 16% |
| Researcher | 6 | 9% |
| Student > Doctoral Student | 5 | 7% |
| Professor > Associate Professor | 4 | 6% |
| Other | 15 | 21% |
| Unknown | 12 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 19 | 27% |
| Engineering | 8 | 11% |
| Psychology | 5 | 7% |
| Agricultural and Biological Sciences | 4 | 6% |
| Nursing and Health Professions | 3 | 4% |
| Other | 18 | 26% |
| Unknown | 13 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 July 2020.
All research outputs
#17,286,645
of 25,374,917 outputs
Outputs from Medical & Biological Engineering & Computing
#1,677
of 2,053 outputs
Outputs of similar age
#124,686
of 187,132 outputs
Outputs of similar age from Medical & Biological Engineering & Computing
#4
of 6 outputs
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