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Building the multivariable model began with inclusion of key variables based on a priori hypotheses (i.e., prior FQ use).

We included Age and APACHE IV pm and all variables with P ≤ 0.20 in the univariable analysis in the multivariable Cox regression model, beginning the day of ICU discharge until death within one year.

We began by fitting a multivariable model including the sociodemographic variables alone, testing for evidence of important interactions.

We began multivariable modelling with a saturated model (A) that included all study variables and product terms.

Risk factors for S. aureus and MRSA colonization were compared with Pearson's chi-squared test (Table  2), and a multivariable logistic regression model was constructed in a reverse step-wise fashion to analyze risk factors for S. aureus carriage, beginning with all demographic and population characteristics from Table  2, and maintaining variables with p < 0.20 in the final multivariable model.

eNot in multivariable model.

The final multivariable model is demonstrated in Table 3.

Figure 1 Maximum and minimum intraoperative heart rate – multivariable model.

They were not selected in the first multivariable model.

Statistics—We developed a multivariable model for ICU death.

The result is also extended to multivariable model validation and verified on a multivariable pilot scale process.