Table 3.
Multiple regression model predicting optimal MAP.
Variable | Estimate | 95% CI | P-value |
---|---|---|---|
Study 1 vs. 3 | −6.03 | (−8.6, −3.9) | <0.001 |
Study 2 vs. 3 | −4.95 | (−7.5, −2.4) | <0.001 |
Age | −0.02 | (−0.1, 0.1) | 0.650 |
Female gender | 0.52 | (−1.5, 2.6) | 0.618 |
White ethnicity | −2.73 | (−5.3,−0.21) | 0.034 |
History of tobacco smoking | −0.20 | (−2, 1.6) | 0.823 |
Hypertension | 1.90 | (−0.39,4.2) | 0.104 |
Ca++ channel blocker | 1.84 | (−0.34, 4) | 0.098 |
Diuretics | −1.89 | (−3.8,−0.01) | 0.049 |
Prior carotid endarterectomy | −5.55 | (−10, −0.9) | 0.019 |
Cardiopulmonary bypass duration (per 60 min) | −1.28 | (−2.4, −0.19) | 0.022 |
Final model was selected using backward selection based on AIC (Akaike Information Criterion) from baseline predictors listed in Table 1. Demographic variables (age, gender, ethnicity and smoking history) and study were kept in the model. Model R2=0.1002.