Assessing bias: the importance of considering confounding.

Failure to evaluate demographic and clinical factors as potential confounders can bias your study results and lead to erroneous conclusions. Study design must include the measurement and reporting of such factors. During analysis, the association between such factors and the outcome and your exposure of interest must be explored. A commonly overlooked type of confounding in the surgical literature is confounding by indication. This needs to be dealt with during study design to ensure that treatment groups include patients with the same range of condition severity and that treatment choice is not based on condition severity. In all likelihood, no matter how many variables one adjusts for, there will be residual confounding, possibly by factors that are unknown and cannot be measured.