Narrated and Abridged: There is (No) Evidence for That: Epistemic Problems in Critical Care Medicine

Below is the narrated video of my powerpoint presentation on Epistemic Problems in Critical Care Medicine, which provides a framework for understanding why we have both false positives and false negatives in clinical trials in critical care medicine and why we should be circumspect about our "evidence base" and our "knowledge".  This is not trivial stuff, and is worth the 35 minutes required to watch the narration of the slideshow.  It is a provocative presentation which gives compelling reasons to challenge our "evidence base" in critical care and medicine in general, in ways that are not widely recognized but perhaps should be, with several suggestions about assumptions that need to be challenged and revised to make our models of reality more reliable.  Please contact me if you would like me to give an iteration of this presentation at your institution.

There is (No) Evidence For That: Epistemic Problems in Evidence Based Medicine

Below is a Power Point Presentation that I have delivered several times recently including one iteration at the SMACC conference in Chicago.  It addresses epistemic problems in our therapeutic knowledge, and calls into question all claims of "there is evidence for ABC" and "there is no evidence for ABC."  Such claims cannot be taken at face value and need deeper consideration and evaluation considering all possible states of reality - gone is the cookbook or algorithmic approach to evidence appraisal as promulgated by the User's Guides.  Considered in the presentation are therapies for which we have no evidence, but they undoubtedly work (Category 1 - Parachutes) and therapies for which we have evidence of efficacy or lack thereof (Category 2) but that evidence is subject to false positives and false negatives, for numerous reasons including: the Ludic Fallacy, study bias (See: Why Most Published Research Findings Are False), type 1 and 2 errors, the "alpha bet" (the arbitrary and lax standard used for alpha, namely 0.05), Bayesian interpretations, stochastic dominance of the null hypothesis, inadequate study power in general and that due to delta inflation and subversion of double significance hypothesis testing.  These are all topics that have been previously addressed to some degree on this blog, but this presentation presents them together as a framework for understanding the epistemic problems that arise within our "evidence base."  It also provides insights into why we have a generation of trials in critical care the results of which converge on the null and why positive studies in this field cannot be replicated.