Long-term Prognostic Value of Stress Phase Entropy for Predicting Major Cardiac Events in Patients with Known or Suspected Coronary Artery Disease.

Abstract

Objective　This retrospective study aimed to investigate the long-term prognostic value and risk stratification in Japanese patients with known or suspected coronary artery disease (CAD) using poststress phase entropy, an index of left ventricular (LV) dyssynchrony.Methods　The patients were followed up for six years to confirm their prognosis. The composite endpoint was the onset of major cardiac events (MCEs), including cardiac death, non-fatal myocardial infarction, and severe heart failure requiring hospitalization. Poststress phase standard deviation (SD), bandwidth, and entropy were calculated using a phase analysis with the Heart Risk View-F software program.Patients　The study included 2,421 patients with known or suspected CAD who underwent rest 201Tl and stress 99 mTc-tetrofosmin electrocardiogram-gated (ECG)-gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI).Results　During the follow-up, 293 patients (13%) experienced MCEs. A multivariate analysis showed that age, the summed difference score, estimated glomerular filtration rate, stress LV ejection fraction (EF), and stress entropy were independent predictors of MCEs. A Kaplan-Meier analysis showed significant risk stratification between each group in the stress phase entropy tertiles. The global chi-squared value predicting MCE onset was significantly improved in the model with the summed stress score and stress LVEF plus entropy, but it was comparable in the model with added bandwidth or phase SD.Conclusion　Stress phase entropy derived from ECG-gated SPECT MPI was a strong long-term predictor of MCEs in Japanese patients with CAD (known or suspected) and it is considered to be the most useful left ventricular dyssynchrony index to improve risk stratification over prediction by perfusion and LVEF assessment alone.