Augmented Oscillations in QT Interval Duration Predict Mortality Post Myocardial Infarction Independent of Heart Rate

Figures

• 

  FIGURE 1. Power contributions to QT interval variability. Plots show the spectrograms averaged for non-survivors (A) and survivors (B) post MI. The relative contribution of RR interval variability is shown in blue; the contribution of respiration is shown in orange. While the absolute value of the RR (blue) and respiration (orange) contributions are higher for non-survivors due to the overall increase in QTV in that group, the relative contribution of RR and respiration to QT power is decreased in non-survivors as shown in the pie charts. Notably, the QT power independent of RR and respiration (yellow) is increased and exhibits a clear peak in the low-frequency band.

• 

  FIGURE 2. Mortality of MI patients stratified by QTV and its components. The figure shows the Kaplan–Meier curves of MI patients stratified by (A) total QT variability, (B) percentage of RR contribution to QTV, (C) percentage of respiratory contribution to QTV, and (D) percentage of QTV independent of RR and respiration. The red curve represents patients at higher risk, while the green curve represents those with lower risk. Patients with higher QTV had a higher risk of mortality compared to those with lower QTV (16.8% vs. 5.5%, p < 0.001). Patients with higher QTV independent of RR and respiration also had a higher 5-year mortality rate (15.2% vs. 5.5%, p < 0.001). Finally, the 5-year mortality rate was higher for patients with reduced RR and respiratory contributions to QTV (13.5% vs. 4.8%; 11% vs. 5.7%, respectively). The figure demonstrates the univariate predictive value of QTV and its components is risk stratification.

• 

  FIGURE 3. Mortality of MI patients stratified by the QTV risk score. Kaplan–Meier curves were obtained from the dichotomized multivariable Cox regression model. The red curve represents patients above the cut off value (0.626), while the green curve represents all other patients. Difference between the two curves was tested using the log-rank test (χ2 = 35.2, p = 2.92×10– 9). The figure demonstrates the predictive value of an increase in QTV risk score for identifying patients with a higher risk of mortality post MI.

• 

  FIGURE 4. Subgroup analysis based on LVEF. The figure shows the Kaplan–Meier curves of MI patients stratified by the QTV risk score for subgroups with (A) LVEF ≤ 35% and (B) LVEF > 35%. The 5-year mortality rate was significantly higher in patients with LVEF > 35% who had a high QTV risk score (16% vs. 4%, p = 1.19×10– 7). The QTV risk score was only marginally predictive of mortality in patients with LVEF ≤ 35%. The figure demonstrates the ability of the QTV risk score to further stratify a subgroup at high risk in the group with LVEF > 35%.

• 

  FIGURE 5. Subgroup analysis based on GRACE score. The figure shows the Kaplan–Meier curves of MI patients stratified by the QTV risk score for subgroups with (A) GRACE score < 120 and (B) GRACE score ≥ 120. The QTV risk score was significantly predictive of mortality only in patients with a score ≥ 120, where the 5-year mortality rate was 25% versus 11%, p = 0.0009. The figure demonstrates the ability of the QTV risk score to further stratify a subgroup with a higher risk in the high-risk cohort (GRACE ≥ 120).