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After performing a linear regression, we concluded that both variables are confounders for the primary outcome.
Looking back, we can now identify possible confounders for the failure.
Second, this was an observational study and there exists the potential of unmeasured confounders (for example post-resuscitation lactic acidosis).
Our review further highlights the importance of the consideration of potential confounders for a reliable and valid simultaneous measurement of sCort and sAA.
Pearson correlation was used to identify confounders for the bone variables.
Similarly, we identified gender, current physical activity, alcohol consumption, calcium intake, and BMI as significant confounders for bone turnover markers.
Possible confounders for Boyden chamber invasion data were investigated.
Second, we investigated potential confounders for each univariate model.
We considered these variables as potential confounders for our analyses.
Potential confounders for strength were lean tissue and age.
These could be important confounders for FENO reference values.
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