Linear regression model for γδT cell count.

Linear regression modeling was used to determine the relative impacts of hypertension and stroke on γδT cell counts and to adjust for clinical and demographic factors and potential interactions (for age, race and gender). This revealed that pre–existing hypertension was the significant predictor in the model accounting for γδT cell counts. Coronary artery disease had no effect when entered into the model, nor did smoking history, beta-blocker treatment, or antithrombotic treatment. CI– confidence intervals.