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The paper states: But as someone pointed out to me on Twitter, table 1 shows that 'no change in symptoms' (n = 17) was more common than 'financially unable' (n = 10). So lack of perceived benefit seems to be the primary, not a secondary reason for dropout?

I also think Carson has never done any research on ME/CFS, yet he has been able to comment as an SMC expert on multiple ME/CFS studies. For example: expert reaction to cytokines for Chronic Fatigue Syndrome | Science Media Centre expert reaction to study linking higher levels of antibodies...

I also don't get this. The only statement I see is: "Evidence that there is a large number of replicated and diverse blood biomarkers that differentiate between ME/CFS cases and controls should now dispel any lingering perception that ME/CFSis caused by deconditioning and exercise intolerance...

Because they controlled the FDR at 0.05, the expected proportions of false positives among the 116 significant features is approximately 6 (not 150).

This method controls the false discovery rate (FDR) at 0.05, which is mentioned multiple times in the paper and graphs. It means that among the significant findings, the expected proportion of false positives (the false discoveries) is only 5%. It's not that complicated and standard in large...

The commentary by Prof Kevin McConway (Emeritus Professor of Applied Statistics) seems quite sensible.

I meant chronic unexplained widespread pain which I think is what the fibromyalgia diagnosis is mostly used for (this may differ pre region though). Seems to occur in a similar population to ME/CFS (mostly adult females), and shows some overlap in symptoms but the energy limitations, PEM, POTS...

8% seems far too high but my impression is that it is at least double that of ME/CFS.

I once wrote this: https://www.s4me.info/threads/central-sensitization-a-matter-of-concern.5346/

Thanks for the tag. I wasn't aware of this Italian study. Had a quick look and it seems interesting that the response between melatonin and agomelatonine was so different.

The reason for posting this is that the Dutch government research funder ZonMw has funded a stud on this drug (sonlicromanol) for Long Covid patients. It's led by Michele van Vugt at Amsterdam University...

Abstract Mitochondrial disease incorporates a group of rare conditions with no approved treatment to date, except for Leber hereditary optic neuropathy. Therapeutic options to alleviate the symptoms of mitochondrial disease are urgently needed. Sonlicromanol is a promising candidate, as it...

Agree with others that this study design isn't able to show what the real effect is, but it does give a ceiling to how large the effect might be. I'm assuming that the 40 patients who kept paying for the drug had a better response than the sample as a whole (the paper says that a common reason...

The Nevada study which they used as a validation cohort was originally published in 2016 and discussed here (it highlighted GRIK3 which plays a role in neurotransmission). Genome-wide association analysis identifies genetic variations in subjects with [ME/CFS], 2016, Schlauch et al | Science for ME

1) Important news: there is now a much greater chance than ever before for #MECFS scientists to obtain funding from #HorizonEurope. 2) For the #HorizonEurope call Tackling high-burden for patients and under-researched medical conditions (HORIZON-HLTH-2025-01-DISEASE-07) the Commission has...

This paper comments on this: Reference 21 is: Pooling/bootstrap-based GWAS (pbGWAS) identifies new loci modifying the age of onset in PSEN1 p.Glu280Ala Alzheimer's disease - PubMed Abstract The literature on GWAS (genome-wide association studies) data suggests that very large sample sizes...

Thanks. I suspect this inflates their effect size. Not sure why they didn't simply use cohen's d as the data is quite similar to a normal distribution.

Also note that this study used a submaximal test in contras to previous CPET-studies which I think all used a maximal test.

In table 4 of the paper, they report an effect size for Work rate at the first ventilatory threshold of 0.742. I don't see how it can be that large. I got an estimate of cohen d = 0.44 when using the sd of the difference between CPETs and d = 0.34 when using the poolsed sd of CPET1.

Thanks for the suggestion. The best I got was 57 matches out of 68 using height, age and weight (sex has a lot of NA's in dataset 1 for some reason). Some might be errors in data insertion. For example there's only 1 participant with height 175 cm and weight 74 kg in both datasets but in...