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In model 1 only the individual hepatic markers were entered (univariate).
In the second model, titer against Pg and inflammatory markers were entered as independent variables.
The possible risk factors and biochemical markers were entered as independent variables in a stepwise linear regression analysis.
All the hepatic markers were entered into the model as continuous variables and the ORs calculated referring to the risk of diabetes per one SD increment in them.
In the original model, all markers were entered as restricted cubic splines with knots at the tertiles to allow a non-linear relationship with outcome.
The receptor for hyaluronic acid-mediated motility and CD8+ TILs, determined to be the most valuable markers, were entered into a second multivariable analysis along with clinicopathological features that are available at the time before surgery, namely pT stage, pN stage and age at diagnosis (Table 3).
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ORs were calculated first in a univariate model in which only the individual hepatic marker was entered and then in 3 other models where HOMA-IR, CRP and common diabetes risk factors were also entered.
For independent association between individual blood markers and stroke outcome, each natural log-transformed (log) blood marker was entered into a separate model after adjusting for age and initial NIHSS score.
The difference between the measured value and the true value (the error) was entered as the outcome variable in the models, while marker number and position were entered as the predictor variables.
Genotypes were expressed as allelic dosage, which is the number of copies of the minor allele, such that genotypes were entered into a marker matrix W as a decimal number in the interval [0, 2].
Inflammatory markers, global CVD risk, and CVD risk factors were entered as independent variables, with each measure of vascular function entered separately as the dependent variable.
More suggestions(15)
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