Serial heart rhythm complexity changes in patients with anterior wall ST segment elevation myocardial infarction

Sci Rep. 2017 Mar 2:7:43507. doi: 10.1038/srep43507.

Abstract

Heart rhythm complexity analysis has been shown to have good prognostic power in patients with cardiovascular disease. The aim of this study was to analyze serial changes in heart rhythm complexity from the acute to chronic phase of acute myocardial infarction (MI). We prospectively enrolled 27 patients with anterior wall ST segment elevation myocardial infarction (STEMI) and 42 control subjects. In detrended fluctuation analysis (DFA), the patients had significantly lower DFAα2 in the acute stage (within 72 hours) and lower DFAα1 at 3 months and 12 months after MI. In multiscale entropy (MSE) analysis, the patients had a lower slope 5 in the acute stage, which then gradually increased during the follow-up period. The areas under the MSE curves for scale 1 to 5 (area 1-5) and 6 to 20 (area 6-20) were lower throughout the chronic stage. Area 6-20 had the greatest discriminatory power to differentiate the post-MI patients (at 1 year) from the controls. In both the net reclassification improvement and integrated discrimination improvement models, MSE parameters significantly improved the discriminatory power of the linear parameters to differentiate the post-MI patients from the controls. In conclusion, the patients with STEMI had serial changes in cardiac complexity.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Arrhythmias, Cardiac / etiology*
  • Arrhythmias, Cardiac / physiopathology*
  • Biomarkers
  • Case-Control Studies
  • Echocardiography
  • Electrocardiography
  • Female
  • Humans
  • Male
  • Middle Aged
  • Myocardium / metabolism
  • Myocardium / pathology
  • ROC Curve
  • ST Elevation Myocardial Infarction / complications*
  • ST Elevation Myocardial Infarction / diagnosis*
  • ST Elevation Myocardial Infarction / metabolism
  • ST Elevation Myocardial Infarction / physiopathology

Substances

  • Biomarkers