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The metabolites identified by multivariate analysis were selected according to their Q-values, which are P-values adjusted for the false discovery rate (FDR).
The response variables in the studies, analysed by multivariate analysis, were the zeta potential and the change in particle size.
Significant risk factors identified by multivariate analysis were recurrent infections (OR = 2.93), presence of artificial nutrition (OR = 3.99), and recent exposure to quinolones (OR = 4.39), third- or fourth-generation cephalosporin (OR = 3.49) and the combination of both antibiotic classes (OR = 5.50).
Independent outcome predictors by multivariate analysis were age, first shockable rhythm, bystander-initiated resuscitation, and I/T-G ratio.
Significant factors for survival by multivariate analysis were gender, ISS stage, number of FISH abnormalities and extramedullary disease.
All risk factors that were identified by multivariate analysis were included in the final multivariate analysis (Final Model; middle column in Figure 2).
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The discriminative ability of variables identified to predict neurological outcome by multivariate analysis was evaluated using receiver operating characteristic (ROC) curves with the corresponding AUC.
More detailed analysis of parameters selected by multivariate analysis was performed using conventional statistical tests.
Analysis of the delay to ICU admission by multivariate analysis is presented in Table 3.
This protective effect was significant after confounding by multivariate analysis was controlled for.
Univariate logistic regression analysis, followed by multivariate analysis was used to identify predictors of one-year mortality.
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