Statistical analysis
REGRESSION, DISEASE
No statistical sample size calculation was performed, and sample size was equal to the number of patients admitted to the participating ICUs during the study. Categorical variables were expressed as frequencies and percentages, and continuous variables were expressed as medians and first and third quartiles (Q1-Q3). To compare baseline characteristics between groups, we used chi-square or Fisher’s exact tests for categorical variables and the Mann-Whitney U for continuous variables. All tests were two-tailed, and significance was set at To investigate possible hospital-level or inter-hospital variation in ICU mortality (as random effects), we used multilevel logistic regression analysis with a conditional random intercept model [All patients were classified as intubated within the first day of ICU stay or thereafter. The first time recorded for the purpose of the study was the day of ICU admission, but all patients were censored within the first 7 days after ICU admission and were discarded to avoid immortal time bias. Propensity score (PS) using the genetic matching algorithm was used to reduce selection bias and balance the covariance matrix of both groups. The match was 1:1 with replacement and ties, and no calibrators. The variables selected for inclusion in the matching model were the variables related to outcome. These variables included demographic characteristics and comorbidities, disease severity and laboratory data.To investigate the association between baseline (ICU admission) variables and early or late intubation, a multivariate analysis (binary logistic regression) was performed. The multivariate model comprised factors of clinical interest and all significant covariates in the univariate analysis. The results are presented as odds ratios (OR) and 95% confidence intervals (CI).Finally, to confirm the results, a survival analysis (Cox hazard regression) was performed to investigate whether survival time was related to covariates, and to estimate the effect size of intubation timing and ICU mortality in the PS matched cohort. The results are presented as hazard ratio (HR) and 95% confidence intervals (CI).SPSS version 24 (IBM Corp. Armonk, NY, USA) and R software (cran.r-project.org) were used for the data analyses.