Table 6. Logistic regression analysis of independent predictors for post-stroke infections.
| Effect | Parameter estimation | Standard | p-value | ||
| Estimate | 95% Confidence Interval | error | |||
| Lower | Upper | ||||
| Model | |||||
| Treatment | 0.015 | ||||
| Interaction: treatment and HLA-DR | 0.036 | ||||
| Estimates | |||||
| Intercept | −12.7 | −38.4 | 13.1 | 13.1 | 0.336 |
| Treatment | 47.2 | 9.0879 | 85.4014 | 19.5 | 0.015 |
| HLA-DR level in verum arm | 1.113 | −1.4563 | 3.6827 | 1.311 | 0.396 |
| HLA-DR level in placebo arm | −3.507 | −6.3319 | −0.6822 | 1.441 | 0.015 |
Shown are the nominal p-values and estimates for the parameters remaining in the model after backward selection. Factors and covariates included for selection were: NIHSS at admission, age, tube feeding, mechanical ventilation, HLA-DR expression (Day 1), treatment, and interaction between treatment and HLA-DR (Day 1) expression. The final logistic model was: log( p/1-p) = μ+treatment+ßtreatment *log(HLA-DR); p: number of infected patients within 11 days/total number of patients (in the respective treatment group).