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  1. Simon M

    Increased risk of chronic fatigue syndrome following burn injuries, 2018, Tsai et al

    The instants rate of 1.6 cases per thousand = 0 .16% new cases per year. That is implausibly hi given that prevalence (two cases) is around 0.2%. So I would agree that this is not measuring ME/CFS, particularly as they didn’t do a proper diagnosis. There I would be extremely interested to see...
  2. Simon M

    Erythrocyte Deformability As a Potential Biomarker for Chronic Fatigue Syndrome, Davis et al (2018)

    Perfectly put. I am concerned about this claim: it would explain how they get such a small P value from the tiny sample, but that P value does not tell you how likely the finding is to hold up in the wider patient population. On the letter is what we need to know. There is another issue. IIRC...
  3. Simon M

    Erythrocyte Deformability As a Potential Biomarker for Chronic Fatigue Syndrome, Davis et al (2018)

    This looks very interesting, but I am eager to see the full text. The P values are astonishing low for such a small sample size (n = 9). For example: “ME/CFS patients had higher entry time (~12%, p<0.0001)” Normally, a mere 12% difference would not lead to such an extreme P value. This...
  4. Simon M

    Stanford Community Symposium 2018: Phair, Metabolic traps, Tryptophan trap

    @RDP Let me echo @Trish's thanks to you for joining the forum and the discussion (it's great to have researchers here) and add my own thanks for the detailed responses to my many questions. I'd like to respond to a few of your points, grouped below into a few themes: Focusing on individual...
  5. Simon M

    Stanford Community Symposium 2018: Phair, Metabolic traps, Tryptophan trap

    Thanks. Perhaps it would help if I summarise my questions here (modified after the helpful feedback, esp from @alex3619 and @Ravn). 1. Biology of causing ME/CFS 1.1 How do kynurenine, serotonin (and NAD?) leads to ME/CFS, particularly given the limited gene expression of IDO 2 (see below)...
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