Deep phenotyping of post-infectious myalgic encephalomyelitis/chronic fatigue syndrome, 2024, Walitt et al

you can test for normality and test for equality of variances and then triage each feature to different tests depending on whether parametric/nonparametric or variance equality, can give you more statistical power while still being rigorous

is covered for excel here in figures 6 & 7 https://pubs.rsc.org/en/content/articlelanding/2020/mo/d0mo00087f

 

Thanks. I'll see if I can parse that, but these concepts are getting a bit advanced for my beginner stats knowledge.

 

If you install realstats addin for excel and use the formulae as in the paper, it will do everything for you automatically so you need not worry about the theory being over your head to execute it. In terms of concepts the embedded image is from the paper and is amazing at helping to understand the logic.

If you'd like some help feel free to email me D.Missailidis@latrobe.edu.au

You've been given good advice anyway (when in doubt, mann-whitney U test! no assumptions made) not trying to micromanage etc

 

Something that seems to happen a lot in ME research is that the patient group shows much more variance than the healthy controls (as in the red group compared to the blue group here: most of the red lines slope sharply up or down while most of the blue lines stay nearly horizontal), but then the results are averaged to cancel out any differences and the conclusion is that there are 'no differences'.

I'm sure it's statistically sound but I can't help wondering if something's being missed!

 

I have forgotten my statistics, but if someone said that a family where everyone was either four foot tall or eight foot tall was statistically indistinguishable from a family where everyone was six foot tall is not doing the right statistics.

 

Difference might be a little more visually apparent if normalizing based on fat free mass (order is baseline total, baseline sleep, day 1 total, day 1 sleep, day 2 total, day 2 sleep, day 3 total, day 3 sleep)



Here's the fat free mass for each group:

(Edit: I accidentally posted the wrong mass chart at first.)

I did notice the study's figure in the post above has one feature that is statistically significant for the metabolic chamber study, respiratory quotient on the 3rd day (p=0.01). (MECFS: 0.87 +- 0.04, HV: 0.89 +- 0.01)

 

https://twitter.com/user/status/1844138469008023558



* slides manhole cover out of the way

* pokes head out and looks around

Hey, today would be just as good a day as any to retract the NIH Intramural Study on ME/CFS

* lowers head

* slides manhole cover back into place

 

Interesting, but I think Walitt still misses a subtle but crucial point, with his comment here:-

“Rather than physical exhaustion or a lack of motivation, fatigue may arise from a mismatch between what someone thinks they can achieve and what their bodies perform.”

I'm no medical expert at all when it come to physiology, but I do have some background in control systems, and they seem to be saying there could be a physical dysfunction somewhere in the motor-control signalling from the brain, which to me seems a very reasonable possibility. A bit like the way your central heating responds if you increase the thermostat temperature, the signal from the thermostat ends up telling the boiler to turn on and the right valve to open, and you end up with heat energy flowing to the radiators. But if any part of that signalling path gets broken or compromised, then it won't happen and the thermostat's request for more heat will be ignored.

But crucially: No matter whether it is the signalling mechanism that is broken, or the boiler itself, the end result is still the same - a physical malfunction that has stopped heat energy getting to the radiators.

So I think it is completely fallacious to say "fatigue may arise from a mismatch between what someone thinks they can achieve and what their bodies perform". That is rubbish to my mind. If the signalling is broken then the body is broken, and cannot perform! The person cannot do it because ... they cannot do it! No matter what they think, or may try to rethink.

Any kind of energy control system has its signalling as an intrinsic part of its functionality, and for a human you cannot, with word play, separate out the signalling as if it is part of the "thinking" process.

Unless I've misunderstood something here.

 

Understood perfectly I would say.

Walitt makes the Cartesian error of the psychologist who thinks you can talk of 'someone' as if they were a component in a system separate from the dynamics of that system. The mechanics may be subtle but 'someone' ultimately describes an integral part of those dynamics. It is the BPS people who are the dualists. In modern science and systems theory you cannot talk of a 'someone' as some sort of wand-waving appendage.

 

He's also forgetting that if someone believes his theory and keeps pushing they get worse and worse.

He doesn't address that the 'mismatch' gets bigger and bigger over time not smaller.

There's no solution from him there. In his mind he is thinking it's easy to ignore or just a form of sensitisation which will get better over time.

He's not admitting that in reality the 'gap' just gets bigger and bigger. My guess would be that he thinks once someone 'knows' it is a mismatch then they can safely and easier ignore it.

When I do that I drop things, fall over, trip over things and become too weak to even use a fork to eat without missing my mouth. It's dangerous.

 

I'm not sure "forgetting" is the right word. To me it feels more like wilful ignorance. I'm not saying that all psychiatry/psychology is bad/wrong, because I know that some aspects of it can be very beneficial to people, with some very genuine and caring practitioners of it. But there seems to be whole massive chunks of their knowledge domain that are build on houses of cards and totally flawed, and those practitioners seem far more interested in preserving their flawed pseudo-science, than in being real scientists and learning from their mistakes. And I have no time for them, because many lives are destroyed by this.

 

I'm starting to wonder if there was a methodological issue with the CSF metabolite lab test in the NIH study. 92% (Edit: 88%) of the 445 chemicals tested had a lower median in ME/CFS. All of the metabolites they reported as significant were lower.



I don't know enough about the field, but does anyone know if most/all of the metabolites in the chart above have a reason to be correlated to each other? It seems too high to be due to chance, but that's just a feeling, could be wrong. Is there any physiological reason this could happen?

I made a chart to visualize the skew. This is just the difference in medians between the two groups for each metabolite. It's probably not ideal for comparing individual metabolites to each other, but it gives an idea of how many are higher vs lower.


I mean, if that's not lab error, then it looks like something very significant just in the combination of all metabolites.

Edit: Or a histogram:

That looks like a normal distribution, just shifted left by about 0.25 for some reason.

Edit 2: And just to double check if this could be due to chance: The mean of the differences is -0.233. I did a Shapiro-Wilk test, these differences are normally distributed (p = 1.35e-16) (Edit: They are not normally distributed. I mistakenly thought low p-value meant normal.), and then a one sample t-test with a null hypothesis mean of 0, and it is significantly different (p = 2.08e-72).

Edit 3: This might be a better way to visualize it, showing the metabolite concentrations for each group separately.

The mean of all median concentrations for ME/CFS is 0.785. For HV it is 1.02. ME/CFS values seem to be shifted down by about 0.234.

Edit 4: I realized I counted changes of zero as downregulated in the "92% downregulated" figure. The correct numbers are 88% downregulated, 4% zero difference, 8% upregulated.

 

I was having a look through the supplementary data and here's another item that I don't think we've covered, that seems weird. Page 6 of the supplementary data —

No surprise pwME score highly on a somatisation scale that looks at —

But what's with the Fatigue Catastrophizing Scale? I would assume HCs should be close to zero, not 13.2, with pwME at 21.1.

Walitt et al reference as [80] Fatigue in Women Receiving Adjuvant Chemotherapy for Breast Cancer: Characteristics, Course, and Correlates (1999, Journal of Pain and Symptom Management) —

That paper doesn't mention "Fatigue Catastrophizing Scale" but does use the word "catastraphizing" twice —

The 1999 paper's methods record —

However a paper from Jan 2024, Psychometric properties of the Fatigue Catastrophizing Scale in a general population and its clinical utility in schizophrenia and breast cancer patients (2024, Fatigue: Biomedicine, Health & Behavior), says —

[17] is The Pain Catastrophizing Scale: Development and Validation (1995, Psychological Assessment)

(Pain isn't present in all 13 items so not a 1:1 mapping.) Anyhow, by a somewhat convoluted path, that would give us (in its originally stated matrix order and my italics for the mapping) —

Rumination
11. I keep thinking about how badly I want the fatigue to stop.
8. I anxiously want the fatigue to go away.
9. I can't seem to keep it out of my mind.
10. I keep thinking about how much it exhausts me.

Magnification
13. I wonder whether something serious may happen.
6. I become afraid that the fatigue may get worse.
7. I think of other fatiguing experiences.

Helplessness
2. I feel I can't go on.
3. It's terrible and I think it's never going to get any better.
1. I worry all the time about whether the fatigue will end.
4. It's awful and I feel that it overwhelms me.
5. I feel I can't stand it any more.
12. There is nothing I can do to reduce the intensity of the fatigue.

For the 13 items, scoring would presumably be equivalent to —

So range is 0 to 52.

How does a healthy control score much >0 on that inventory?

 

the whole concept of "catastrophizing" does not seem appropraite for people who are actually sick. The scales seem to presume that the fatigue or pain or whatever is not so bad as to warrant "catastrophizing." These scales have been used by the Chalders of the world to psycho-pathologize sick people. They tie it in with "fear avoidance" behavior, which to them represens "catastrophizing" rather than people having a realistic appraisal of their fatigue/pain symptoms and how they respond to activities. The idea that sick people are catastrophising is like blaming them for being sick and blaming their sickness on the fact that they are purportedly catastrophizing. Their reasoning is backwards.

 

In England if a female person walks down the street with a neutral or unhappy expression on her face, she might find herself being told to ‘Smile!’ or directed to ‘Give us a smile then!’ by a male person that she happens to pass by. Or she might hear him say ‘Cheer up love it might never happen!’

The barer of this instruction doesn’t need to know whether or not the recipient is currently experiencing or already has had a non smile or a sad face type experience. Or whether being given unsolicited instructions for one’s facial muscles by randoms or else a possibility of this happening, might be a neutral or sad face experience of itself.

This is the academic version.

 

Below is the sample PCS questionnaire from the user's manual. As can be seen it is introduced with the phrase "We are interested in the types of thoughts and feeling that you have when you are in pain". The question is - how did they introduce their version of the fatigue-related scale? Was it, again, just a simple substitution of phrases involving "pain" with "fatigue"? If so, then the participants may have been thinking about a time when they were feeling fatigued whilst answering the questionnaire which would explain why healthy controls have such scores.



ETA: There is an article from last year which examined the psychometric properties of this "Fatigue Catastrophizing Scale" (Fatigue Biomed Health Behav 12(1):58–71). Haven't looked at it yet.

 

Referring to CSF observations above: does anyone know if the ME/CFS participants and healthy volunteers were tested at different times, in two distinct groups? Whether for just the CSF metabolite concentrations, or the study as a whole.

 

The more you look at this paper the weirder it gets.