Litcius/Paper detail

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

David Sidebotham

2020Anaesthesia31 citationsDOI

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.

Topics & Concepts

MedicineBayes' theoremContrast (vision)Clinical trialRelative riskIntensive care medicineBayesian probabilityStatisticsInternal medicineConfidence intervalArtificial intelligenceComputer scienceMathematicsCardiac, Anesthesia and Surgical OutcomesMeta-analysis and systematic reviewsHemodynamic Monitoring and Therapy