| Site . | AUC . | Optimal probability threshold . | Accuracy . | Sensitivity . | Specificity . |
|---|---|---|---|---|---|
| Overall | 0.922 (0.910, 0.934) | 0.11a | 86.9% (85.8%, 87.8%) 4030/4640 | 82.8% (79.9%, 85.4%) 640/773 | 87.7% (86.6%, 88.7%) 3390/3867 |
| 0.18b | 89.2% (88.3%, 90.1%) 4139/4640 | 80.6% (77.6%, 83.3%) 623/773 | 90.9% (90.0%, 91.8%) 3516/3867 | ||
| Bern | 0.835 (0.782, 0.887) | 0.11a | 87.2% (86.0%, 88.3%) 2978/3416 | 62.1% (49.3%, 73.8%) 41/66 | 87.7% (86.5%, 88.8%) 2937/3350 |
| 0.07b | 83.3% (82.0%, 84.5%) 2844/3416 | 68.2% (55.6%, 79.1%) 45/66 | 83.6% (82.3%, 84.8%) 2799/3350 | ||
| Oxford | 0.900 (0.869, 0.931) | 0.11a | 78.4% (74.1%, 82.2%) 330/421 | 73.7% (68.4%, 78.5%) 224/304 | 90.6% (83.8%, 95.2%) 106/117 |
| 0.04b | 84.6% (80.7%, 87.9%) 356/421 | 83.9% (79.3%, 87.8%) 255/304 | 86.3% (78.7%, 92.0%) 101/117 | ||
| Seoul | 0.948 (0.933, 0.964) | 0.11a | 89.9% (87.6%, 91.9%) 722/803 | 93.1% (90.1%, 95.3%) 375/403 | 86.8% (83.0%, 89.9%) 347/400 |
| 0.18b | 90.4% (88.2%, 92.4%) 726/803 | 91.6% (88.4%, 94.1%) 369/403 | 89.2% (85.8%, 92.1%) 357/400 |
| Site . | AUC . | Optimal probability threshold . | Accuracy . | Sensitivity . | Specificity . |
|---|---|---|---|---|---|
| Overall | 0.922 (0.910, 0.934) | 0.11a | 86.9% (85.8%, 87.8%) 4030/4640 | 82.8% (79.9%, 85.4%) 640/773 | 87.7% (86.6%, 88.7%) 3390/3867 |
| 0.18b | 89.2% (88.3%, 90.1%) 4139/4640 | 80.6% (77.6%, 83.3%) 623/773 | 90.9% (90.0%, 91.8%) 3516/3867 | ||
| Bern | 0.835 (0.782, 0.887) | 0.11a | 87.2% (86.0%, 88.3%) 2978/3416 | 62.1% (49.3%, 73.8%) 41/66 | 87.7% (86.5%, 88.8%) 2937/3350 |
| 0.07b | 83.3% (82.0%, 84.5%) 2844/3416 | 68.2% (55.6%, 79.1%) 45/66 | 83.6% (82.3%, 84.8%) 2799/3350 | ||
| Oxford | 0.900 (0.869, 0.931) | 0.11a | 78.4% (74.1%, 82.2%) 330/421 | 73.7% (68.4%, 78.5%) 224/304 | 90.6% (83.8%, 95.2%) 106/117 |
| 0.04b | 84.6% (80.7%, 87.9%) 356/421 | 83.9% (79.3%, 87.8%) 255/304 | 86.3% (78.7%, 92.0%) 101/117 | ||
| Seoul | 0.948 (0.933, 0.964) | 0.11a | 89.9% (87.6%, 91.9%) 722/803 | 93.1% (90.1%, 95.3%) 375/403 | 86.8% (83.0%, 89.9%) 347/400 |
| 0.18b | 90.4% (88.2%, 92.4%) 726/803 | 91.6% (88.4%, 94.1%) 369/403 | 89.2% (85.8%, 92.1%) 357/400 |
95% confidence intervals are shown in parentheses.
aOptimal AI-ECG probability threshold as defined in the algorithm derivation cohort.
bArtificial intelligence electrocardiogram probability threshold as optimized for each cohort using the Youden index method.
| Site . | AUC . | Optimal probability threshold . | Accuracy . | Sensitivity . | Specificity . |
|---|---|---|---|---|---|
| Overall | 0.922 (0.910, 0.934) | 0.11a | 86.9% (85.8%, 87.8%) 4030/4640 | 82.8% (79.9%, 85.4%) 640/773 | 87.7% (86.6%, 88.7%) 3390/3867 |
| 0.18b | 89.2% (88.3%, 90.1%) 4139/4640 | 80.6% (77.6%, 83.3%) 623/773 | 90.9% (90.0%, 91.8%) 3516/3867 | ||
| Bern | 0.835 (0.782, 0.887) | 0.11a | 87.2% (86.0%, 88.3%) 2978/3416 | 62.1% (49.3%, 73.8%) 41/66 | 87.7% (86.5%, 88.8%) 2937/3350 |
| 0.07b | 83.3% (82.0%, 84.5%) 2844/3416 | 68.2% (55.6%, 79.1%) 45/66 | 83.6% (82.3%, 84.8%) 2799/3350 | ||
| Oxford | 0.900 (0.869, 0.931) | 0.11a | 78.4% (74.1%, 82.2%) 330/421 | 73.7% (68.4%, 78.5%) 224/304 | 90.6% (83.8%, 95.2%) 106/117 |
| 0.04b | 84.6% (80.7%, 87.9%) 356/421 | 83.9% (79.3%, 87.8%) 255/304 | 86.3% (78.7%, 92.0%) 101/117 | ||
| Seoul | 0.948 (0.933, 0.964) | 0.11a | 89.9% (87.6%, 91.9%) 722/803 | 93.1% (90.1%, 95.3%) 375/403 | 86.8% (83.0%, 89.9%) 347/400 |
| 0.18b | 90.4% (88.2%, 92.4%) 726/803 | 91.6% (88.4%, 94.1%) 369/403 | 89.2% (85.8%, 92.1%) 357/400 |
| Site . | AUC . | Optimal probability threshold . | Accuracy . | Sensitivity . | Specificity . |
|---|---|---|---|---|---|
| Overall | 0.922 (0.910, 0.934) | 0.11a | 86.9% (85.8%, 87.8%) 4030/4640 | 82.8% (79.9%, 85.4%) 640/773 | 87.7% (86.6%, 88.7%) 3390/3867 |
| 0.18b | 89.2% (88.3%, 90.1%) 4139/4640 | 80.6% (77.6%, 83.3%) 623/773 | 90.9% (90.0%, 91.8%) 3516/3867 | ||
| Bern | 0.835 (0.782, 0.887) | 0.11a | 87.2% (86.0%, 88.3%) 2978/3416 | 62.1% (49.3%, 73.8%) 41/66 | 87.7% (86.5%, 88.8%) 2937/3350 |
| 0.07b | 83.3% (82.0%, 84.5%) 2844/3416 | 68.2% (55.6%, 79.1%) 45/66 | 83.6% (82.3%, 84.8%) 2799/3350 | ||
| Oxford | 0.900 (0.869, 0.931) | 0.11a | 78.4% (74.1%, 82.2%) 330/421 | 73.7% (68.4%, 78.5%) 224/304 | 90.6% (83.8%, 95.2%) 106/117 |
| 0.04b | 84.6% (80.7%, 87.9%) 356/421 | 83.9% (79.3%, 87.8%) 255/304 | 86.3% (78.7%, 92.0%) 101/117 | ||
| Seoul | 0.948 (0.933, 0.964) | 0.11a | 89.9% (87.6%, 91.9%) 722/803 | 93.1% (90.1%, 95.3%) 375/403 | 86.8% (83.0%, 89.9%) 347/400 |
| 0.18b | 90.4% (88.2%, 92.4%) 726/803 | 91.6% (88.4%, 94.1%) 369/403 | 89.2% (85.8%, 92.1%) 357/400 |
95% confidence intervals are shown in parentheses.
aOptimal AI-ECG probability threshold as defined in the algorithm derivation cohort.
bArtificial intelligence electrocardiogram probability threshold as optimized for each cohort using the Youden index method.
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