Literature DB >> 32255517

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

D Sidebotham1.   

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.
© 2020 Association of Anaesthetists.

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

Year:  2020        PMID: 32255517     DOI: 10.1111/anae.15029

Source DB:  PubMed          Journal:  Anaesthesia        ISSN: 0003-2409            Impact factor:   6.955


  2 in total

Review 1.  Bayes' formula: a powerful but counterintuitive tool for medical decision-making.

Authors:  M P K Webb; D Sidebotham
Journal:  BJA Educ       Date:  2020-04-19

2.  In Defense of Science.

Authors:  David Sidebotham
Journal:  J Extra Corpor Technol       Date:  2021-12
  2 in total

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