Table 1.
Baseline clinical characteristics of UK Biobank sample by predicted heart rate recovery tertile
| Clinical characteristic | HRRpred tertile |
|||
|---|---|---|---|---|
| Total sample |
Tertile 1 |
Tertile 2 |
Tertile 3 |
|
| N = 56,793 | N = 18,931 | N = 18,931 | N = 18,931 | |
| Age, years | 57.1 (8.1) | 57.8 (8.1) | 57.5 (8.1) | 56.1 (8.2) |
| Men, n (%) | 27,578 (49%) | 10,947 (58%) | 8834 (47%) | 7797 (41%) |
| Race, n (%) | ||||
| White | 51,977 (91%) | 17,382 (91%) | 17,389 (91%) | 17,206 (91%) |
| Black | 1539 (3%) | 507 (3%) | 477 (3%) | 555 (3%) |
| Other | 3277 (6%) | 1042 (6%) | 1065 (6%) | 1170 (6%) |
| Body mass index, kg/m2 | 27.4 (4.4) | 29.2 (4.7) | 27.3 (4.1) | 25.7 (3.6) |
| Systolic blood pressure, mm Hg | 137 (17) | 141 (16) | 138 (17) | 134 (17) |
| Hypertension treatment, n (%) | 11,131 (20%) | 5395 (29%) | 3477 (18%) | 2259 (12%) |
| Diabetes mellitus, n (%) | 1225 (2%) | 722 (4%) | 348 (2%) | 155 (1%) |
| Current smoker, n (%) | 4708 (8%) | 1750 (9%) | 1517 (8%) | 1441 (8%) |
| Total cholesterol, mmol/L | 5.7 (4.9, 6.4) | 5.7 (4.9, 6.5) | 5.7 (5.0, 6.5) | 5.7 (5.0, 6.4) |
| HDL cholesterol, mmol/L | 1.4 (1.2, 1.7) | 1.3 (1.1, 1.6) | 1.4 (1.2, 1.7) | 1.5 (1.3, 1.8) |
| Lipid-lowering therapy | 10,141 (18%) | 4634 (25%) | 3243 (17%) | 2264 (12%) |
| Prevalent CVD, n (%) | 1521 (3%) | 543 (3%) | 546 (3%) | 432 (2 %) |
| Prevalent heart failure, n (%) | 136 (0.2%) | 71 (0.4 %) | 43 (0.2%) | 22 (0.1%) |
| Prevalent atrial fibrillation, n (%) | 757 (1%) | 291 (2%) | 262 (1%) | 204 (1%) |
| Resting heart rate, bpm | 71 (63, 79) | 81 (75, 88) | 70 (65, 75) | 62 (57, 67) |
| Observed HRR at 50 seconds, bpm | 27 (21, 34) | 22 (16, 28) | 28 (22, 33) | 32 (26, 38) |
| Predicted HRR at 50 seconds, bpm | 28 (25, 31) | 23 ( 21, 25) | 28 (27, 29) | 33 (31, 34) |
Data are expressed as n (%), mean (standard deviation), or median (25th, 75th percentile) as appropriate.
CVD = cardiovascular disease; HDL = high-density lipoprotein; HRR = heart rate recovery; HRRpred = predicted HRR from resting electrocardiogram convolutional neural network model.