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Having had a quick look at the original paper, it seems that this measure (sometimes called FInsm5 or spectral fatigue index) is not used very often and was never validated in patient groups. I also haven't found a study that reports it like in the paper by Walitt and colleagues: 'the slope of...

This recent Japanese study also used the Dimitrov index, although they call it the spectral fatigue index (SFI). They tested 15 collegiate male athletes underwent three nonexplosive back squat tasks comprising low, medium, and high volumes. There was a significant relationship between Rate of...

This study tested the Dimitrov Index: "The log FInsm5 as a single parameter predictor accounted for 37% of the performance variance of changes in muscle power" but this was in 15 healthy participants who did 10 leg presses with 2 minutes in between. EMG spectral indices and muscle power fatigue...

So, if I understand correctly muscle fatigue manifests itself on electromyography (EMG) by an increase in amplitude and a shift towards lower frequencies. A bit like a cyclist tends to use a bigger gear and fewer resolutions when he is fatigued. Ratios between high and low frequency ranges have...

Yes I might be a typo because when trying to do a t-test of all participants' slope, I got the same results they report namely t =32 and p = 0.008. I think the most straightforward approach would be to use a linear mixed effect model that tests for the interaction of patient_group and blocks...

Their Sas code looks like this: https://github.com/docwalitt/National-Institutes-of-Health-Myalgic-Encephalomyelitis-Chronic-Fatigue-Syndrome-Code-Repository/blob/main/EEfRT/EEfRT%20Hard%20Task%20Choice%20Proc%20GEE.sas

So they did exclude those with a choice time of 5 seconds. @Nitro802 @andrewkq I reran the Python GEE analysis I did before and now got the exact same result as theirs: (OR) = 1.652 [1.029, 2.653], p = 0.038. So the minor difference (I previously got an OR of 1.60) was due to those with a...

I noticed that 2 weeks ago Walitt et al. have added new files on EEfRT to the code Github repository for the study that were not there before. https://github.com/docwalitt/National-Institutes-of-Health-Myalgic-Encephalomyelitis-Chronic-Fatigue-Syndrome-Code-Repository/tree/main/EEfRT The Readme...

If I try to do this using statsmodels in python I get: t = 3.1995698023875945, p-value = 0.007638634835067758 There is one NaN (for HV-5 blok 5) and in my calculation I simply ignored this value.

If you click on 'Source Data' in the Walitt et al. paper you find the data behind the figures. For figure 4B you get the data for each of the participants for 5 blocks (the first , the last before fatigue and the first three after fatigue). In the graph they seem to have plotted the means per...

These look like the main results:

These seem to be the main results: So the (small) ME/CFS group had lower hair cortisol than the healthy and arthritis but pervious studies have not found consistent results. The authors write:

In the data and graphs I used, no. I suspect Walitt et al. did not exclude them either because they don't mention this in the paper and the data sheet says that those with 5s choice time had valid data (Valid Data_is_1 = 1). If I remember correctly, Treadway et al. said that these should be...

No I initially used the number of hard task divided by the total number of trials because that is easier to interpret. I suspect they use this ratio because odds are easier to work with in statistical modelling but when plotting the raw data I think that dividing by the total number of trials...

There's also this graph that shows the mean of hard task choices per group as the trials progressed, originally posted here: https://www.s4me.info/threads/use-of-eefrt-in-the-nih-study-deep-phenotyping-of-pi-me-cfs-2024-walitt-et-al.37463/page-24#post-520344

Hope that this is what you mean:

I think so. Without excluding those 5, the controls would have a higher amount of 'virtual rewards': https://www.s4me.info/threads/use-of-eefrt-in-the-nih-study-deep-phenotyping-of-pi-me-cfs-2024-walitt-et-al.37463/page-33#post-537825

What do you mean by PHTC?

This seems like an important point. I think they should have done a sensitivity analysis and report in the discussion how the data looks like if they maintained the same requirements (might have overlooked this but couldn't find it in the paper). Hopefully we will get access to the data so that...

I've asked him the following: Could you explain why you think fitness matching is not a good idea? If many CPET measurements are collinear with VO2peak, doesn't this suggest that differences could be due to deconditioning rather than ME/CFS? I would think that fitness matching makes...