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Surgical treatments are half as likely as medical therapies to be based on randomized controlled trial (RCT) evidence.1 The paucity of randomized surgical trials may reflect ethical challenges to randomization, insufficient funding and insufficient knowledge and infrastructure in surgery to conduct large, full-scale and definitive trials. Many surgical events, such as scapholunate dissociation as compared with hypertension, are relatively rare; this undoubtedly accounts for part of the discrepancy. As a result, most surgical research uses retrospective designs, often with a small number of patients.1 Despite efforts to design a methodologically sound surgical technique study and perform proper statistical analyses, the results may not accurately reflect the true situation. This is a major concern in observational studies of surgical interventions. Whenever one observes an association between an exposure, such as a surgical intervention, and an outcome measure, one is tempted to derive a causal inference when, in fact, the relation may not be causal. The exposure could be a risk factor causing harm or a protective factor preventing harm. For example, one may detect an increased rate of postoperative wound infection in patients who undergo open appendectomy compared with those who have a laparoscopic procedure and presume that the type of approach (open surgery in this case) is a risk factor for the increased postoperative wound infections. However, this association may simply be owing to the presence of a third factor or a confounding factor, such as obesity (as shown further on), which ought to be controlled for at the stages of design or analysis.2 Failure to control for confounders in a study undermines its credibility and internal validity.

Confounding: What is it and how do we deal with it?