Premium
Are most randomised trials in anaesthesia and critical care wrong? An analysis using Bayes’ theorem
Author(s) -
Sidebotham D.
Publication year - 2020
Publication title -
anaesthesia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.839
H-Index - 117
eISSN - 1365-2044
pISSN - 0003-2409
DOI - 10.1111/anae.15029
Subject(s) - medicine , bayes' theorem , contrast (vision) , clinical trial , relative risk , intensive care medicine , bayesian probability , statistics , confidence interval , mathematics , artificial intelligence , computer science
Summary 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.