Table 3.
Multivariable Cox regression analysis predicting incident cardiovascular events
| A. Diabetes Covariates |
Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | Model 7 |
|---|---|---|---|---|---|---|---|
| Clinic SBP (10 mmHg) |
1.20* (1.02-1.41) |
0.95 (0.76-1.17) |
0.92 (0.74-1.16) |
1.01 (0.83-1.23) |
0.93 (0.74-1.16) |
1.20* (1.02-1.41) |
1.18 (1.00-1.40) |
| 24-hour SBP (10 mmHg) |
1.44** (1.15-1.80) |
||||||
| Awake SBP (10 mmHg) |
1.48** (1.16-1.89) |
1.29 (0.92-1.82) |
|||||
| Sleep SBP (10 mmHg) |
1.32** (1.10-1.58) |
1.15 (0.90-1.47) |
|||||
| Non-dipping† (yes=1, no=0) |
1.85 (0.85-4.05) |
||||||
| Non-dipper vs. dipper |
1.60 (0.67-3.83) |
||||||
| Riser vs. dipper | 2.55 (0.88-7.33) |
||||||
| −2log likelihood | 270.5 | 261.4 | 261.4 | 262.3 | 260.1 | 268.0 | 267.4 |
| χ 2 | - | 9.1 | 9.1 | 8.2 | 10.4 | 2.5 | 3.1 |
| P value | - | 0.003 | 0.003 | 0.004 | 0.006 | 0.11 | 0.08 |
| B. Non-diabetes Covariatess |
Model 1 | Model 2 | Model 3 | Model 4 | Model 5 | Model 6 | Model 7 |
|---|---|---|---|---|---|---|---|
| Clinic SBP (10 mmHg) |
1.18** (1.05-1.33) |
1.03 (0.88-1.20) |
1.07 (0.92-1.25) |
1.09 (0.94-1.25) |
1.06 (0.91-1.23) |
1.18** (1.05-1.33) |
1.17* (1.04-1.32) |
| 24-hour SBP (10 mmHg) |
1.32** (1.10-1.58) |
||||||
| Awake SBP (10 mmHg) |
1.19* (1.01-1.40) |
1.10 (0.90-1.34) |
|||||
| Sleep SBP (10 mmHg) |
1.20* (1.03-1.39) |
1.14 (0.95-1.37) |
|||||
| Non-dipping† (yes=1, no=0) |
1.30 (0.79-2.11) |
||||||
| Non-dipper vs. dipper |
1.04 (0.61-1.80) |
||||||
| Riser vs. dipper | 2.39* (1.23-4.65) |
||||||
| −2log likelihood | 845.0 | 835.7 | 840.0 | 839.3 | 838.4 | 843.9 | 838.8 |
| χ 2 | - | 9.3 | 5.0 | 5.7 | 6.6 | 1.1 | 6.2 |
| P value | - | 0.002 | 0.03 | 0.02 | 0.04 | 0.29 | 0.01 |
Values are hazard ratios (95% CI), per 10 mmHg difference in SBP.
P<0.05,
P<0.01,
P<0.001
SBP indicates systolic blood pressure.
Non-dipping includes true non-dippers and risers. Each model was adjusted for age, sex, BMI, smoking, and serum creatinine. Comparison of log-likelihood functions, based on chi-square distribution are shown as −2 log likelihood and χ2 in the bottom of each model. The −2 log likelihood and χ2 indicate improvement vs. Model 1 for clinic SBP. The p-values indicate for the improvements in the model when awake and/or sleep ambulatory BP are added to the equations, which were highly significant, and their significance levels were essentially the same as those of the regression estimate for the ABP measure.