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A multivariable regression (including age, sex, mechanism, occupation, place of injury, mode of arrival, and distance) looking at outcome of death in the hospital did not show any correlation with any variables except for KTS, where each lower KTS point was correlated with a decrease of 5% in the chance of survival (95% CI, 4.9%–5.7%).
The sixth column shows the multivariable regression including all variables, besides the ones excluded due to perceived multicollinearity.
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Age and sex-adjusted regressions were followed by multivariable regressions including all variables for which a relationship was supported in bivariable analysis (full model).
Further multivariable regressions included simultaneous adjustment for all three SES variables and covariates in order to evaluate independent associations between SES variables and WOMAC outcomes.
We used multivariable linear regression, including adjusting for pre-pregnancy body mass index, to calculate relative change in GWG and 95% CI.
The primary outcome will be analyzed using multivariable Poisson regression, including random effects and clustering of patients by site and treating physician.
Multivariable logistic regression including demographic and genetic variables and Kaplan-Meier survival analyses of genotype frequencies and pregnancy outcome were performed.
We used multivariable logistic regression, including a random effect for cluster to account for the collection of data from discrete slum localities.
Table 2 presents the results of a three-term multivariable logistic regression including HRD-LOH, HRD-TAI, and HRD-LST scores as predictors of BRCA1/2 deficiency.
Table 4 shows the results of the multivariable logistic regression including the overall motivation and job satisfaction scales as well as demographic and work-related factors.
On multivariable logistic regression including all univariable predictors, only functional class and presence of liver or renal dysfunction remained in the model.
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