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These two factors remained significant after adjustment for confounding by age and sex in the multivariable analysis model.
A multivariable analysis model is presented for secondary outcome.
We selected age as the covariate in multivariable analysis model 1.
This article attempts to inform the debate by a multivariable analysis model.
The TIMP-1 remained prognostic for survival in a multivariable analysis model that included performance status, risk group and other biomarkers.
The first multivariable analysis model included baseline glycemia measures to examine whether they related to the chosen outcome measures (model 1).
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Two multivariable analysis models were examined.
Variables found to be significant at the p < 0.10 were included in the final multivariable analysis models.
In the multivariable analysis models, a manual stepwise backwards elimination process was used to identify factors that were significantly associated with the study outcomes using 5% significance level.
In the multivariable analysis models, we adjusted these confounders to investigate the individual effect of VAP on medical expenses and utilization.
In the multivariable analysis models, a manual procedure of stepwise backward elimination process was used to identify factors that were significantly associated with the study outcomes using 5%% significance level.
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