Are most randomised trials in anaesthesia and critical care wrong? An analysis using Bayes' theorem

Abstract

False findings are an inevitable consequence of statistical testing. In this article, I use Bayes' theorem to estimate the false positive and false negative risks for randomised controlled trials related to our speciality. For small trials in peri-operative medicine, the false positive risk appears to be at least 50%. For trials reporting weakly significant p values, the risk is even higher. By contrast, large, multicentre trials in critical care appear to have a high false negative risk. These findings suggest much of the evidence that underpins our clinical practice is likely to be wrong.

Keywords: Bayes’ theorem; anaesthesia; critical care; probability; risk.