Dogma and Pseudoaxioms


  • Dogma is a belief generally held to be true by a group, organisation or professional body that is put forth as authoritative without adequate grounds.
  • Axioms are universally accepted principles or rules.
  • Pseudoaxioms, like pseudoscience, are “false principles or rules often handed down from generation to generation of medical providers and accepted without serious challenge or investigation” (Newman, 2007)
  • “It is everyone’s responsibility to find out how to ask questions systematically, find answers from searching the literature, critically appraise the literature and apply the results to practice” (Bellomo, 2011)

The greater the ignorance the greater the dogmatism

Osler W. Chauvinism in Medicine


Each of the following pseudoaxioms either lacks supportive evidence or has been disproved

  • “cricoid pressure is useful during rapid sequence intubation due to risk of aspiration”
  • “epinephrine-containing local anaesthetics in ring blocks must be avoided for digital anaesthesia due to the risk of gangrene”
  • “avoid administration of opioids to the patient with undifferentiated abdominal pain because it interferes with diagnosis”
  • “calcium must be avoided in chronic digoxin toxicity due to the risk of causing a ‘stone heart'”
  • “septal haematoma causes necrosis of the septal cartilage unless urgently treated”
  • “early oral feeding after colorectal surgery is dangerous”
  • “immediate fluid resuscitation saves lives in penetrating torso injuries”


  • “a logical theory often trumps reality” (Newman, 2007)
  • doctors need internal dogma to function, uncertainty around major medical and surgical procedures impairs their performance and ability to obtain consent
  • pseudoaxioms are often based on case reports and anecdotes
  • immediate physiological gain (surrogate outcomes) may not translate into patient-orientated clinically significant outcomes
  • lack of awareness of data
  • neglect to examine or seriously consider the available evidence
  • root literature gets misinterpreted each time it is referenced by secondary literature (“Chinese Whispers” aka “The Telephone Game”)
  • peer behaviours become a practice pattern, and these norms are difficult to break – in fact, there is a usually a benefit to preventing rogue behaviour
  • medicolegally, appropriate treatment is defined by what is reasonable to a body of peers
  • scientific facts have a ‘half-life’ — findings published in high impact, highly cited journals are more likely to be overturned by subsequent research (termed “medical reversal”)
  • how scientists and clinicians appraise evidence from clinical research is affected by interpretation biases
  • current publication practices may distort science
  • it is easier to stick to received dogma in a state of permanent flux, doctors are not good at “unlearning”


Based on Young et al (2008), the following economic factors are at play:

  • Winner’s curse
    • the small proportion of results chosen for publication are unrepresentative of scientists’ repeated samplings of the real world
  • Oligopoly
    • a few journals with the highest impact factors rule the roost; publication outside of these amounts to being consigned to oblivion
  • Artificial scarcity
    • any situation where even though a commodity exists in abundance, restrictions of access, distribution, or availability make it seem rare, and thus overpriced
    • with journals “page space” is used to confer selectivity, low acceptance rates creates the illusion of a meritocracy.
  • Herding
    • the actions of a few prominent individuals rather than the cumulative input of many independent agents drives people’s valuations of a commodity (in this case, an area of research)
  • Uncertainty
    • usually, we do not know what information will be most useful (valuable) eventually
  • Branding
    • branding is marking the product as valuable
    • it is important when a commodity cannot easily be assigned much intrinsic value and when we fear the exchange environment will be flooded with an overabundance of redundant, useless, and misleading product


Based on Ioannidis 2005 (see the reference for a detailed explanation):

  • A published positive result is more likely to be true than false if (1 – β)R > 0.05 (assuming the study uses an alpha value of p = 0.05)
  • R is the ratio of the number of “true relationships” to “no relationships” among those tested in a field of research, and varies depending on whether the field targets highly likely or unlikely relationships
  • in reality, the probability of being false is even greater than calculated due to bias and due to multiple independent researchers studying the same or similar questions


  • The smaller the studies conducted in a scientific field, the less likely the research findings are to be true
  • The smaller the effect sizes in a scientific field, the less likely the research findings are to be true
  • The greater the number and the lesser the selection of tested relationships in a scientific field, the less likely the research findings are to be true
  • The greater the flexibility in designs, definitions, outcomes, and analytical modes in a scientific field, the less likely the research findings are to be true
  • The greater the financial and other interests and prejudices in a scientific field, the less likely the research findings are to be true
  • The hotter a scientific field (with more scientific teams involved), the less likely the research findings are to be true

For instance, an adequately powered RCT with a small amount of bias and prior odds of 1:1 has a PPV = 0.85 — most studies are far worse, and a PPV exceeding 50% is quite difficult to get.


According to Richard Smith, BMJ blog 2013:

  • ‘a recent study by Amgen of preclinical studies showed that 80-90% could not be replicated’
  • In epidemiology: ‘Odds ratios of over five are seen in only one in 16 studies, almost always in small studies, and with 99% of those studies the effect size shrinks when a larger study is done’

Prasad et al 2013

  • out of the 2004 ‘Original Articles’ published in the New England Journal of Medicine from 2001 to 2010, 363 articles tested an established therapy
  • Of these 146 (40.2%) reversed that practice, whereas 138 (38.0%) reaffirmed it

References and Links


Journal articles

  • Bellomo R. The dangers of dogma in medicine. Med J Aust. 2011 Oct 3;195(7):372-3. PubMed PMID: 21978331.
  • Fatovich DM. Medical reversal: What are you doing wrong for your patient today? Emerg Med Australas. 2013 Feb;25(1):1-3. doi: 10.1111/1742-6723.12044. PubMed PMID: 23379445. [Free Fulltext]
  • Ioannidis JP. Why most published research findings are false. PLoS Med. 2005 Aug;2(8):e124. Epub 2005 Aug 30. PubMed PMID: 16060722; PubMed Central PMCID: PMC1182327.
  • Ioannidis JP, Panagiotou OA. Comparison of effect sizes associated with biomarkers reported in highly cited individual articles and in subsequent meta-analyses. JAMA. 2011 Jun 1;305(21):2200-10. doi: 10.1001/jama.2011.713. PubMed PMID: 21632484. [Free Full Text]
  • Newman DH. Truth, and epinephrine, at our fingertips: unveiling the pseudoaxioms. Ann Emerg Med. 2007 Oct;50(4):476-7. Epub 2007 Aug 24. PubMed PMID: 17719691.
  • Poynard T, Munteanu M, Ratziu V, Benhamou Y, Di Martino V, Taieb J, Opolon P. Truth survival in clinical research: an evidence-based requiem? Ann Intern Med. 2002 Jun 18;136(12):888-95. PubMed PMID: 12069563.
  • Prasad V, Vandross A, Toomey C, Cheung M, Rho J, Quinn S, Chacko SJ, Borkar D, Gall V, Selvaraj S, Ho N, Cifu A. A Decade of Reversal: An Analysis of 146 Contradicted Medical Practices. Mayo Clin Proc. 2013 Jul 12. doi:pii: S0025-6196(13)00405-9. 10.1016/j.mayocp.2013.05.012. [Epub ahead of print] PubMed PMID: 23871230. [Free Full Text] (includes a video commentary by the lead author)
  • Young NS, Ioannidis JP, Al-Ubaydli O. Why current publication practices may distort science. PLoS Med. 2008 Oct 7;5(10):e201. doi: 10.1371/journal.pmed.0050201. PubMed PMID: 18844432; PubMed Central PMCID: PMC2561077.

FOAM and web resources

CCC 700 6

Critical Care


Chris is an Intensivist and ECMO specialist at the Alfred ICU in Melbourne. He is also a Clinical Adjunct Associate Professor at Monash University. He is a co-founder of the Australia and New Zealand Clinician Educator Network (ANZCEN) and is the Lead for the ANZCEN Clinician Educator Incubator programme. He is on the Board of Directors for the Intensive Care Foundation and is a First Part Examiner for the College of Intensive Care Medicine. He is an internationally recognised Clinician Educator with a passion for helping clinicians learn and for improving the clinical performance of individuals and collectives.

After finishing his medical degree at the University of Auckland, he continued post-graduate training in New Zealand as well as Australia’s Northern Territory, Perth and Melbourne. He has completed fellowship training in both intensive care medicine and emergency medicine, as well as post-graduate training in biochemistry, clinical toxicology, clinical epidemiology, and health professional education.

He is actively involved in in using translational simulation to improve patient care and the design of processes and systems at Alfred Health. He coordinates the Alfred ICU’s education and simulation programmes and runs the unit’s education website, INTENSIVE.  He created the ‘Critically Ill Airway’ course and teaches on numerous courses around the world. He is one of the founders of the FOAM movement (Free Open-Access Medical education) and is co-creator of litfl.com, the RAGE podcast, the Resuscitology course, and the SMACC conference.

His one great achievement is being the father of three amazing children.

On Twitter, he is @precordialthump.

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