Table 4.
Model without ECG variables* | Model with ECG variables | |||
---|---|---|---|---|
Cases | <0.50† | 0.50 – 0.69† | ≥ 0.70† | Total |
<0.50 | 79 | 43 | 3 | 125 (39%) |
0.50 – 0.69 | 29 | 61 | 54 | 144 (45%) |
>=0.70 | 0 | 10 | 38 | 48 (15%) |
Total | 108 (34%) | 114 (36%) | 95 (30%) | 317 |
Controls | <0.50 | 0.50 – 0.69 | >= 0.70 | Total |
<0.50 | 175 | 21 | 2 | 198 (62%) |
0.50 – 0.69 | 46 | 47 | 14 | 107 (34%) |
>=0.70 | 0 | 5 | 7 | 12 (4%) |
Total | 221 (70%) | 73 (23%) | 23 (7%) | 317 |
Net reclassification improvement = 22.7%, z = 4.811, p <0.0001
Logistic model included the following terms: EF ≤35% vs. >35%, age, sex, diabetes, and hypertension. In the model with ECG markers, each marker (heart rate, JTc, and QRS) was entered separately as a dichotomous variable (≥75th vs. <75th percentile).
Predicted probabilities from the logistic regression model. Note that when the predicted probability is 0.5, then the two outcomes (SCD or no SCD) are equally likely.
Green colors indicate an improvement in prediction of SCD odds with addition of ECG markers (movement from lower to higher predicted probability for cases, and from higher to lower predicted probability for controls); red colors indicate worsening prediction (movement from higher to lower predicted probability for cases, and from lower to higher predicted probability for controls).