Statistical analysis
REGRESSION
Continuous variables were described as minimum or maximum values, mean and standard deviation (SD), or median and interquartile range (IQR), depending on their clinical relevance and distribution. Dichotomous variables were presented as frequencies and percentages. For the univariate analysis, differences between the intervention groups were assessed with the chi-square test and Fisher's exact test for categorical variables or the student's t-test or Mann–Whitney U test for continuous variables, depending on their distribution.A multivariate logistic regression model was developed in the general cohort to evaluate the relationship between 6 and 12 m mortality (dependent variable) and demographics, comorbid conditions, and laboratory variables (explanatory variables). The logistic regression model included variables with a Finally, we performed a targeted maximum likelihood estimation (TMLE) analysis to simulate a randomised controlled trial using the baseline characteristics to estimate the one-year mortality average effect of macrolide-based treatment in critical patients with CAP admitted to the ICU. TMLE is used for the estimation of causal effects using observational data. TMLE estimates both the outcome and the treatment mechanisms and requires an initial estimate of the conditional expectation of the outcome given the exposure, the covariates, and the probability of being treated given the observed confounders, which is done using ensemble and machine-learning algorithms. Then, it performs a substitution step that optimises the bias-variance trade-off for the average treatment effect (ATE). TMLE calculates the adjusted marginal difference in mean outcome associated with a binary point treatment for continuous or binary outcomes. To estimate the ATE of macrolide treatment, we calculated the marginal risk difference of one-year mortality for patients receiving macrolide-based therapy versus those not receiving it through TMLE. A significance level of 0.05 and a confidence level of 95% were chosen. Data analysis was done using R and SPSS (IBM) version 29.