Use of EEfRT in the NIH study: Deep phenotyping of PI-ME/CFS, 2024, Walitt et al

[Sam Carter]

... Walit et al. report that given equal levels ...

There's one tiny typo in an otherwise fantastic letter @ME/CFS Skeptic, "Walit" should be "Walitt".

 

[Dakota15]

This is fantastic, @ME/CFS Skeptic. I do hope this will find a way to be submitted

 

[Karen Kirke]

I have only skimmed the draft, so just a couple of notes on this particular bit:

I used data shared by @Karen Kirke in this post:
https://www.s4me.info/threads/use-o...s-2024-walitt-et-al.37463/page-19#post-519652

For anyone who wants to quote any calculations based on data available from mapMECFS in a publication, the following must be cited (according to mapMECFS):

Please include the following citations when using these data:

1. Walitt, B., et al. “Deep phenotyping of Post-infectious Myalgic Encephalomyelitis/Chronic Fatigue Syndrome.” Nature Communications. February 21, 2024. DOI: 10.1038/s41467-024-45107-3
   
   
2. Mathur, R.* & Carnes, M.U.*, et al. mapMECFS: a portal to enhance data discovery across biological disciplines and collaborative sites. J Transl Med 19, 461 (2021). https://doi.org/10.1186/s12967-021-03127-3
   *contributed equally and are designated co-first authors

I have amended my original post to include this info as well.

If quoting the particular calculation I did above, then either someone with access to the data should be a co-author and should double-check it (either me or someone else) or include my original post in the references Deep phenotyping of post-infectious myalgic encephalomyelitis/chronic fatigue syndrome, 2024, Walitt et al.

PI-ME/CFS patients were severely disabled with a mean SF-36 physical function score of 31.8 compared to a score of 97.9 for the control group.

If you/others do want to cite my original post in the references, then it may sound like a contradiction - "severely disabled" in the draft text but in my post the mean places the average patient just on the moderate side of the border of moderate and severe ME/CFS. Two different things - disability and ME/CFS - but it could still jump out to any reader who follows the link. You could get around that by using a word other than "severely".

 

[EndME]

I don't know if this thread has just slowed down or if others are working on a letter behind the scenes. I think a lot of valid points were raised that prove that Walitt et al.'s interpretation of the EEfRT data is seriously flawed.

I have written a first draft for a letter to be sent to the authors, asking for a correction. Pretty much all arguments have already been made by others on this thread so I take no credit for them - just want to help to string them toghether.

I have no concrete plan to send the letter. I would prefer that others who have more statistical knowledge and academic qualifications than me will take this further.


Incorrect interpretation of ME/CFS patients’ effort preference
In a comprehensive study of patients with post-infectious myalgic encephalomyelitis/chronic fatigue syndrome (PI-ME/CFS), Walitt et al. claim that “an alteration of effort preference, rather than physical or central fatigue” is a defining feature of the illness.1 Effort preference was defined as “how much effort a person subjectively wants to exert” and measured using the Effort-Expenditure for Rewards Task (EEfRT). The interpretation of EEfRT results by Walitt and colleagues, however, is highly problematic as it fails to consider that tasks required more effort from patients than from healthy controls.

The EEfRT is a multi-trial experiment that has been used to measure reward motivation in patients with anhedonia, schizophrenia, and other mental disorders. In Walitt et al.’s study of 15 PI-ME/CFS and 17 healthy the EEfRT lasted 15 minutes. In each of the successive trials, participants were instructed to choose between an easy and hard task. Both required several button presses within a limited time frame for successful completion: 30 button presses in 7 seconds for the easy task and 98 button presses in 21 seconds for the hard task. If participants completed the hard task successfully, they had a chance of receiving a higher reward than for completing the easy task. The reward values and probability of receiving it varied across trials and this information was provided to participants before they made their choice. Effort preference was estimated by the proportion of hard task choices. Walitt et al. report that given equal levels and probabilities of reward, healthy controls chose more hard tasks than PI-ME/CFS patients (Odds Ratio, OR = 1.65 [1.03, 2.65], p = 0.04).

The EEfRT requires however that participants can complete the tasks successfully and that the effort needed is equivalent in patients and controls. Treadway et al., the research team that developed the EEfRT and whose protocol was implemented by Walitt et al. with minor modifications, cautioned: “An important requirement for the EEfRT is that it measure individual differences in motivation for rewards, rather than individual differences in ability or fatigue. The task was specifically designed to require a meaningful difference in effort between hard and easy-task choices while still being simple enough to ensure that all subjects were capable of completing either task, and that subjects would not reach a point of exhaustion.” 2

Several techniques have been introduced in the EEfRT literature to ensure that the test measures reward motivation rather than differences in effort or ability. These include individually calibrating the required number of button presses3, controlling for participants’ motoric ability4, and evaluating whether participants had an adequate completion rate.2

Although Walitt et al. implemented four test trials before the EEfRT started, they did not implement measures to ensure that the effort required to complete tasks was similar in patients and controls. Consequently, PI-ME/CFS patients could only complete 67% of the hard tasks successfully compared to 98% in controls. This was a much larger difference (OR = 27.23 [6.33, 117.14], p < 0.0001) than the group difference in choosing hard over easy tasks. This problem was already evident in the four test trials during which PI-ME/CFS patients could only complete 42% of the hard tasks compared to 82% for controls. When we added successful completion rate to the statistical model, the difference in hard task choices was no longer significant (OR = 1.19 [0.79, 1.81]).

Walitt et al. did note that during the EEfRT there was no difference in the decline in button-press rate over time for either group for hard tasks. This might indicate that task-related fatigue did not influence the results. There was however a decline in button-press-rate in PI-ME/CFS patients for easy tasks that was not seen in controls. In addition, these measurements only reflect fatigue induced by the 15-minute button-pressing test, not the symptoms and debility participants already had at the start of the EEfRT.

PI-ME/CFS patients were severely disabled with a mean SF-36 physical function score of 31.8 compared to a score of 97.9 for the control group. Reduced psychomotor function5 and impairments in fingertip dexterity and gross movement of the hand, fingers, and arm6 have been reported in ME/CFS patients. Walitt et al. also found that patients in their cohort were unable to maintain force during a hand grip task.1 It is therefore likely that the EEfRT required more effort from PI-ME/CFS patients than from controls. Walitt et al. also reported a strong correlation (R=0.57) between PI-ME/CFS patients’ hard task choices and the ability to maintain force during the grip test. This supports our conclusion that patients’ EEfRT choices reflected motor ability as well as effort preference. No such correlation was found in healthy controls (R=-0.04).

The fact that the group difference in hard task choices was relatively small compared to the larger difference in completion rate, suggests that patients kept trying to succeed on hard tasks, despite past failures. Figure 1 shows the recorded button presses and completion rate per trial for all 31 participants. Several PI-ME/CFS patients had repeated failed attempts to complete the hard tasks (seen as repeated high red bars on the graph), a pattern that was not seen in controls. These findings are contrary to Walitt et al.’s hypothesis that ME/CFS patients prefer to exert themselves less than healthy controls.

View attachment 21419
Figure 1. Button presses per participant for each of the trials they managed to complete during the 15-minute EEfRT. Successful completions are pictured in green while failed attempts are indicated in red.

In conclusion, the EEfRT data indicates that the button-pressing tasks were more difficult for PI-ME/CFS patients than for controls, not that the former have abnormal effort preferences. In the past, ME/CFS patients have repeatedly been ‘victim blamed’ when behavioral consequences of their illness were incorrectly proposed as the cause of their symptoms.7 Considering the negative impact such misattributions may have, we kindly ask Walitt et al to correct their erroneous account of the EEfRT results.

References
1. Walitt, B. et al. Deep phenotyping of post-infectious myalgic encephalomyelitis/chronic fatigue syndrome. Nat Commun 15, 907 (2024).

2. Treadway, M. T., Buckholtz, J. W., Schwartzman, A. N., Lambert, W. E. & Zald, D. H. Worth the ‘EEfRT’? The Effort Expenditure for Rewards Task as an Objective Measure of Motivation and Anhedonia. PLOS ONE 4, e6598 (2009).

3. Fervaha, G. et al. Incentive motivation deficits in schizophrenia reflect effort computation impairments during cost-benefit decision-making. J Psychiatr Res 47, 1590–1596 (2013).

4. Ohmann, H. A., Kuper, N. & Wacker, J. A low dosage of the dopamine D2-receptor antagonist sulpiride affects effort allocation for reward regardless of trait extraversion. Personal Neurosci 3, e7 (2020).

5. Schrijvers, D. et al. Psychomotor functioning in chronic fatigue syndrome and major depressive disorder: a comparative study. J Affect Disord 115, 46–53 (2009).

6. Sanal-Hayes, N. E. M., Hayes, L. D., Mclaughlin, M., Berry, E. C. J. & Sculthorpe, N. F. People with Long Covid and ME/CFS Exhibit Similarly Impaired Dexterity and Bimanual Coordination: A Case-Case-Control Study. Am J Med S0002-9343(24)00091–3 (2024) doi:10.1016/j.amjmed.2024.02.003.

7. Thoma, M. et al. Why the Psychosomatic View on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Is Inconsistent with Current Evidence and Harmful to Patients. Medicina 60, 83 (2024).

That's a great starting point, thanks for getting the discussion going again! I've had to take a quick break, but am still very much looking into the data and analysing it and deciding what response we can write, @andrewkq is still very much involved in this.

 

[EndME]

I don't know if this thread has just slowed down or if others are working on a letter behind the scenes. I think a lot of valid points were raised that prove that Walitt et al.'s interpretation of the EEfRT data is seriously flawed.

I have written a first draft for a letter to be sent to the authors, asking for a correction. Pretty much all arguments have already been made by others on this thread so I take no credit for them - just want to help to string them toghether.

I have no concrete plan to send the letter. I would prefer that others who have more statistical knowledge and academic qualifications than me will take this further.


Incorrect interpretation of ME/CFS patients’ effort preference
In a comprehensive study of patients with post-infectious myalgic encephalomyelitis/chronic fatigue syndrome (PI-ME/CFS), Walitt et al. claim that “an alteration of effort preference, rather than physical or central fatigue” is a defining feature of the illness.1 Effort preference was defined as “how much effort a person subjectively wants to exert” and measured using the Effort-Expenditure for Rewards Task (EEfRT). The interpretation of EEfRT results by Walitt and colleagues, however, is highly problematic as it fails to consider that tasks required more effort from patients than from healthy controls.

The EEfRT is a multi-trial experiment that has been used to measure reward motivation in patients with anhedonia, schizophrenia, and other mental disorders. In Walitt et al.’s study of 15 PI-ME/CFS and 17 healthy the EEfRT lasted 15 minutes. In each of the successive trials, participants were instructed to choose between an easy and hard task. Both required several button presses within a limited time frame for successful completion: 30 button presses in 7 seconds for the easy task and 98 button presses in 21 seconds for the hard task. If participants completed the hard task successfully, they had a chance of receiving a higher reward than for completing the easy task. The reward values and probability of receiving it varied across trials and this information was provided to participants before they made their choice. Effort preference was estimated by the proportion of hard task choices. Walitt et al. report that given equal levels and probabilities of reward, healthy controls chose more hard tasks than PI-ME/CFS patients (Odds Ratio, OR = 1.65 [1.03, 2.65], p = 0.04).

The EEfRT requires however that participants can complete the tasks successfully and that the effort needed is equivalent in patients and controls. Treadway et al., the research team that developed the EEfRT and whose protocol was implemented by Walitt et al. with minor modifications, cautioned: “An important requirement for the EEfRT is that it measure individual differences in motivation for rewards, rather than individual differences in ability or fatigue. The task was specifically designed to require a meaningful difference in effort between hard and easy-task choices while still being simple enough to ensure that all subjects were capable of completing either task, and that subjects would not reach a point of exhaustion.” 2

Several techniques have been introduced in the EEfRT literature to ensure that the test measures reward motivation rather than differences in effort or ability. These include individually calibrating the required number of button presses3, controlling for participants’ motoric ability4, and evaluating whether participants had an adequate completion rate.2

Although Walitt et al. implemented four test trials before the EEfRT started, they did not implement measures to ensure that the effort required to complete tasks was similar in patients and controls. Consequently, PI-ME/CFS patients could only complete 67% of the hard tasks successfully compared to 98% in controls. This was a much larger difference (OR = 27.23 [6.33, 117.14], p < 0.0001) than the group difference in choosing hard over easy tasks. This problem was already evident in the four test trials during which PI-ME/CFS patients could only complete 42% of the hard tasks compared to 82% for controls. When we added successful completion rate to the statistical model, the difference in hard task choices was no longer significant (OR = 1.19 [0.79, 1.81]).

Walitt et al. did note that during the EEfRT there was no difference in the decline in button-press rate over time for either group for hard tasks. This might indicate that task-related fatigue did not influence the results. There was however a decline in button-press-rate in PI-ME/CFS patients for easy tasks that was not seen in controls. In addition, these measurements only reflect fatigue induced by the 15-minute button-pressing test, not the symptoms and debility participants already had at the start of the EEfRT.

PI-ME/CFS patients were severely disabled with a mean SF-36 physical function score of 31.8 compared to a score of 97.9 for the control group. Reduced psychomotor function5 and impairments in fingertip dexterity and gross movement of the hand, fingers, and arm6 have been reported in ME/CFS patients. Walitt et al. also found that patients in their cohort were unable to maintain force during a hand grip task.1 It is therefore likely that the EEfRT required more effort from PI-ME/CFS patients than from controls. Walitt et al. also reported a strong correlation (R=0.57) between PI-ME/CFS patients’ hard task choices and the ability to maintain force during the grip test. This supports our conclusion that patients’ EEfRT choices reflected motor ability as well as effort preference. No such correlation was found in healthy controls (R=-0.04).

The fact that the group difference in hard task choices was relatively small compared to the larger difference in completion rate, suggests that patients kept trying to succeed on hard tasks, despite past failures. Figure 1 shows the recorded button presses and completion rate per trial for all 31 participants. Several PI-ME/CFS patients had repeated failed attempts to complete the hard tasks (seen as repeated high red bars on the graph), a pattern that was not seen in controls. These findings are contrary to Walitt et al.’s hypothesis that ME/CFS patients prefer to exert themselves less than healthy controls.

View attachment 21419
Figure 1. Button presses per participant for each of the trials they managed to complete during the 15-minute EEfRT. Successful completions are pictured in green while failed attempts are indicated in red.

In conclusion, the EEfRT data indicates that the button-pressing tasks were more difficult for PI-ME/CFS patients than for controls, not that the former have abnormal effort preferences. In the past, ME/CFS patients have repeatedly been ‘victim blamed’ when behavioral consequences of their illness were incorrectly proposed as the cause of their symptoms.7 Considering the negative impact such misattributions may have, we kindly ask Walitt et al to correct their erroneous account of the EEfRT results.

References
1. Walitt, B. et al. Deep phenotyping of post-infectious myalgic encephalomyelitis/chronic fatigue syndrome. Nat Commun 15, 907 (2024).

2. Treadway, M. T., Buckholtz, J. W., Schwartzman, A. N., Lambert, W. E. & Zald, D. H. Worth the ‘EEfRT’? The Effort Expenditure for Rewards Task as an Objective Measure of Motivation and Anhedonia. PLOS ONE 4, e6598 (2009).

3. Fervaha, G. et al. Incentive motivation deficits in schizophrenia reflect effort computation impairments during cost-benefit decision-making. J Psychiatr Res 47, 1590–1596 (2013).

4. Ohmann, H. A., Kuper, N. & Wacker, J. A low dosage of the dopamine D2-receptor antagonist sulpiride affects effort allocation for reward regardless of trait extraversion. Personal Neurosci 3, e7 (2020).

5. Schrijvers, D. et al. Psychomotor functioning in chronic fatigue syndrome and major depressive disorder: a comparative study. J Affect Disord 115, 46–53 (2009).

6. Sanal-Hayes, N. E. M., Hayes, L. D., Mclaughlin, M., Berry, E. C. J. & Sculthorpe, N. F. People with Long Covid and ME/CFS Exhibit Similarly Impaired Dexterity and Bimanual Coordination: A Case-Case-Control Study. Am J Med S0002-9343(24)00091–3 (2024) doi:10.1016/j.amjmed.2024.02.003.

7. Thoma, M. et al. Why the Psychosomatic View on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Is Inconsistent with Current Evidence and Harmful to Patients. Medicina 60, 83 (2024).

My guess is that the authors will probably respond to such a letter with something along the lines of "inability to complete tasks does not predict lower choice of hard tasks for pwME within this trial, indeed those with the lowest completetion rate chose hard most often in pwME, as such we have shown that these results are due to "effort preference" and not due to lower completion rates".

I'm still analysis bits and pieces of the data to see what can be found...

 

[ME/CFS Skeptic]

I've had to take a quick break, but am still very much looking into the data and analysing it and deciding what response to write, so is @andrewkq I believe.

Great news! I unfortunately (due to personal circumstances) will not be able to sign or co-sign a letter as I prefer to remain anonymous. So I hope that you, Andrew and others can take this further. Feel free to use or change anything from the draft above (I'm also happy to help out with further research and analysis behind the scenes if needed).

When we added successful completion rate to the statistical model, the difference in hard task choices was no longer significant (OR = 1.19 [0.79, 1.81]).

I think I made an error here because Andrew did not add successful completion rate to the model as I initially thought but a new binary category 'hard_task_completer' that refers to having a success rate of hard tasks above 90% (1) or not (0).

My guess is that the authors will probably respond to such a letter with something along the lines of "inability to complete tasks does not predict lower choice of hard tasks for pwME within this trial, indeed those with the lowest completetion rate chose hard most often in pwME, as such we have shown that these results are due to "effort preference" and not due to lower completion rates".

Yes good point. Perhaps it's worth a try to add the actual completion rates to the model, not just having a +90% completion rate. Maybe that results in a clearer correlation.

If not, then I think the explanation is that many patients kept trying on the hard task, despite repeated failure (so the opposite of their view that ME/CFS patients have lower effort preferences). The tasks were much harder for ME/CFS patients (resulting in a large difference in completion rate) but the difference in hard task choices was relatively small because patients compensated by being more motivated, more willing to try, more willing to spend effort etc. And that weakened the correlation between the two. That would be my guess.

 

[rvallee]

I don't know if this thread has just slowed down or if others are working on a letter behind the scenes. I think a lot of valid points were raised that prove that Walitt et al.'s interpretation of the EEfRT data is seriously flawed.

I have written a first draft for a letter to be sent to the authors, asking for a correction. Pretty much all arguments have already been made by others on this thread so I take no credit for them - just want to help to string them toghether.

EDIT: I unfortunately will not be able to sign or co-sign a letter as (due to personal circumstances) I prefer to remain anonymous at the moment.
I thus have no concrete plan to send the letter. I hope that others who have more statistical knowledge and academic qualifications than me will take this further.

Incorrect interpretation of ME/CFS patients’ effort preference
In a comprehensive study of patients with post-infectious myalgic encephalomyelitis/chronic fatigue syndrome (PI-ME/CFS), Walitt et al. claim that “an alteration of effort preference, rather than physical or central fatigue” is a defining feature of the illness.1 Effort preference was defined as “how much effort a person subjectively wants to exert” and measured using the Effort-Expenditure for Rewards Task (EEfRT). The interpretation of EEfRT results by Walitt and colleagues, however, is highly problematic as it fails to consider that tasks required more effort from patients than from healthy controls.

The EEfRT is a multi-trial experiment that has been used to measure reward motivation in patients with anhedonia, schizophrenia, and other mental disorders. In Walitt et al.’s study of 15 PI-ME/CFS and 17 healthy the EEfRT lasted 15 minutes. In each of the successive trials, participants were instructed to choose between an easy and hard task. Both required several button presses within a limited time frame for successful completion: 30 button presses in 7 seconds for the easy task and 98 button presses in 21 seconds for the hard task. If participants completed the hard task successfully, they had a chance of receiving a higher reward than for completing the easy task. The reward values and probability of receiving it varied across trials and this information was provided to participants before they made their choice. Effort preference was estimated by the proportion of hard task choices. Walitt et al. report that given equal levels and probabilities of reward, healthy controls chose more hard tasks than PI-ME/CFS patients (Odds Ratio, OR = 1.65 [1.03, 2.65], p = 0.04).

The EEfRT requires however that participants can complete the tasks successfully and that the effort needed is equivalent in patients and controls. Treadway et al., the research team that developed the EEfRT and whose protocol was implemented by Walitt et al. with minor modifications, cautioned: “An important requirement for the EEfRT is that it measure individual differences in motivation for rewards, rather than individual differences in ability or fatigue. The task was specifically designed to require a meaningful difference in effort between hard and easy-task choices while still being simple enough to ensure that all subjects were capable of completing either task, and that subjects would not reach a point of exhaustion.” 2

Several techniques have been introduced in the EEfRT literature to ensure that the test measures reward motivation rather than differences in effort or ability. These include individually calibrating the required number of button presses3, controlling for participants’ motoric ability4, and evaluating whether participants had an adequate completion rate.2

Although Walitt et al. implemented four test trials before the EEfRT started, they did not implement measures to ensure that the effort required to complete tasks was similar in patients and controls. Consequently, PI-ME/CFS patients could only complete 67% of the hard tasks successfully compared to 98% in controls. This was a much larger difference (OR = 27.23 [6.33, 117.14], p < 0.0001) than the group difference in choosing hard over easy tasks. This problem was already evident in the four test trials during which PI-ME/CFS patients could only complete 42% of the hard tasks compared to 82% for controls. When we added successful completion rate to the statistical model, the difference in hard task choices was no longer significant (OR = 1.19 [0.79, 1.81]).

Walitt et al. did note that during the EEfRT there was no difference in the decline in button-press rate over time for either group for hard tasks. This might indicate that task-related fatigue did not influence the results. There was however a decline in button-press-rate in PI-ME/CFS patients for easy tasks that was not seen in controls. In addition, these measurements only reflect fatigue induced by the 15-minute button-pressing test, not the symptoms and debility participants already had at the start of the EEfRT.

PI-ME/CFS patients were severely disabled with a mean SF-36 physical function score of 31.8 compared to a score of 97.9 for the control group. Reduced psychomotor function5 and impairments in fingertip dexterity and gross movement of the hand, fingers, and arm6 have been reported in ME/CFS patients. Walitt et al. also found that patients in their cohort were unable to maintain force during a hand grip task.1 It is therefore likely that the EEfRT required more effort from PI-ME/CFS patients than from controls. Walitt et al. also reported a strong correlation (R=0.57) between PI-ME/CFS patients’ hard task choices and the ability to maintain force during the grip test. This supports our conclusion that patients’ EEfRT choices reflected motor ability as well as effort preference. No such correlation was found in healthy controls (R=-0.04).

The fact that the group difference in hard task choices was relatively small compared to the larger difference in completion rate, suggests that patients kept trying to succeed on hard tasks, despite past failures. Figure 1 shows the recorded button presses and completion rate per trial for all 31 participants. Several PI-ME/CFS patients had repeated failed attempts to complete the hard tasks (seen as repeated high red bars on the graph), a pattern that was not seen in controls. These findings are contrary to Walitt et al.’s hypothesis that ME/CFS patients prefer to exert themselves less than healthy controls.

View attachment 21419
Figure 1. Button presses per participant for each of the trials they managed to complete during the 15-minute EEfRT. Successful completions are pictured in green while failed attempts are indicated in red.

In conclusion, the EEfRT data indicates that the button-pressing tasks were more difficult for PI-ME/CFS patients than for controls, not that the former have abnormal effort preferences. In the past, ME/CFS patients have repeatedly been ‘victim blamed’ when behavioral consequences of their illness were incorrectly proposed as the cause of their symptoms.7 Considering the negative impact such misattributions may have, we kindly ask Walitt et al to correct their erroneous account of the EEfRT results.

References
1. Walitt, B. et al. Deep phenotyping of post-infectious myalgic encephalomyelitis/chronic fatigue syndrome. Nat Commun 15, 907 (2024).

2. Treadway, M. T., Buckholtz, J. W., Schwartzman, A. N., Lambert, W. E. & Zald, D. H. Worth the ‘EEfRT’? The Effort Expenditure for Rewards Task as an Objective Measure of Motivation and Anhedonia. PLOS ONE 4, e6598 (2009).

3. Fervaha, G. et al. Incentive motivation deficits in schizophrenia reflect effort computation impairments during cost-benefit decision-making. J Psychiatr Res 47, 1590–1596 (2013).

4. Ohmann, H. A., Kuper, N. & Wacker, J. A low dosage of the dopamine D2-receptor antagonist sulpiride affects effort allocation for reward regardless of trait extraversion. Personal Neurosci 3, e7 (2020).

5. Schrijvers, D. et al. Psychomotor functioning in chronic fatigue syndrome and major depressive disorder: a comparative study. J Affect Disord 115, 46–53 (2009).

6. Sanal-Hayes, N. E. M., Hayes, L. D., Mclaughlin, M., Berry, E. C. J. & Sculthorpe, N. F. People with Long Covid and ME/CFS Exhibit Similarly Impaired Dexterity and Bimanual Coordination: A Case-Case-Control Study. Am J Med S0002-9343(24)00091–3 (2024) doi:10.1016/j.amjmed.2024.02.003.

7. Thoma, M. et al. Why the Psychosomatic View on Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Is Inconsistent with Current Evidence and Harmful to Patients. Medicina 60, 83 (2024).

Fantastic letter. I hope it gets published. Can a letter be published as coming from the forum itself? Without names?

 

[EndME]

@Hutan I for example looked at the highest amount of hard rounds played in a row per player (for the first 35 rounds, excluding HV F).

For the HV you get the numbers: 2 2 2 3 5 3 12 2 2 5 2 4 2 2 5 5
For ME/CFS you get the numbers: 3 2 5 5 3 5 1 6 2 2 5 2 4 2 2

That means the mean of the highest amount of hard rounds played in a row (for the first 35 rounds) for HVs is 3.625 whilst for pwME it is 3.2, a small difference driven by HV H (the same HV H that also largely drives the end results of the study, i.e. the higher mean in choosing hard).

Of course this one statistic really captures very little or close to nothing of the dynamics of the game and how often one has to take breaks.

If you look at the highest amount of hard rounds played in a row that were won per player (for the first 35 rounds, without HV F) you would expect something more significant because pwME have a much lower percentage of completion of hard tasks. That is also precisely what you get.

For the HV you get the idential numbers: 2 2 2 3 5 3 12 2 2 5 2 4 2 2 5 5
For ME/CFS you get the numbers: 1 1 5 1 3 5 1 1 2 5 2 4 2 2
That means the mean of highest amount of hard rounds successfully completed in a row (for the first 35) rounds for HVs is 3.625 whilst for pwME it is 2.3, which is a rather large difference which already shows us quite a bit.

Now these number don't cover nearly the full "rhythm-dynamics" in which the game is played because people play hard multiple times, more often than just the one time they do their maximum and so forth. It's a bit more complicated to try to capture the full dynamics of taking "breaks". The easiest thing would be too look at the above but instead of taking just the maximum per player you take all of the occurrences, i.e. whenever someone plays hard more than once in a row you count how often that happens in a row and add all of those occurences up, that's something I haven't done yet. Alternatively one easily could look at how often do people go from easy to hard in total.

I did "come up" with a metric, that is conceptually easy, but very time consuming to implement, to capture the full dynamics of each players "breaks" which ends up giving you one final value (a number) for the amount of "breaks" for each player takes and which does account for the rhythm in which the game is played in (rather than just "playing easy=one break"). For that you plot graphs per player for the number of times people play hard/easy as the game progresses, the y axis will cature your dynamics and the x axis is just the rounds of trials. If someone plays hard multiple times in a row they get added +1 on that graph for all of those games from where they were previously standing and the first time someone goes to easy you then add -1 to their current value for that game. If they continue with easy they are given the additional value -1 (which is the difference between playing hard multiple times where you don't accumulate +1's, but for easy you do accumulate -1's, because the end metric is supposed to count the pauses/breaks you need), if they go with easy again then you go to -2, if they then play hard you go up by +1 and so forth. The metric one then uses to count the breaks per player is something mathematics call total variation and essentially measures the total height of your graph. You can then add up all total varitations of the individual players to get the mean for each group (ME/CFS and HV). You do the same thing for games in a row as well as games succesfully played in a row (with the difference here being that successes for easy count the same way as just choosing easy, since both are a break).

I'm somewhat confident this captures taking "breaks" reasonably well over the full duration of the game (but I still have to think about it properly and am not even sure about if the whole thing does what you want it to do) and gives you one number at the end of everything that also captures the dynamics of the game (I'm also fairly confident I explained it very badly and posting a graph would better explain what I mean). I think one will be able to come up with something better or even something better by just looking at the easy rounds, because these are the breaks, but I haven't really come up with something yet that also accounts for the rhythm in which the game is played. I also still have to think about whether the above thing is the right way to go about this and whether it really captures everything you want to capture and if that is even meaningful at all.

Whether that would end up giving you something valuable I currently don't know, especially because the variation in what pwME do in this trial is so high and there is no obvious "rhythm" in how the game is played rather than just different people doing completely different things.

The end idea would probably be to have some notion "how often does someone have to take breaks but yet still choose to do hard, even if he can't". But I'm not sure if any of the above means anything and I'm guessing that it doesn't, because the whole setup of the game is very unrobust.

Before diving deeper into the dynamics, i.e. rhythms and breaks of the game, I had one closer look at the values "highest amount of hard rounds played in a row that were won per player (for the first 35 rounds)" and looked at the relationship between this and "effort preference" i.e. the choice to go hard more often.

Since the differences were rather big between both groups (mean for ME: 2.3, mean for HV:3.6) I thought this would be worthy of at least another look. Since I hadn't posted the values before, the variance for "highest amount of hard rounds played in a row that were won per player (for the first 35 rounds)" is higher in HV (SD is 2.5) than it is in ME (SD is 1.5), which is what you expect since HV H represents a large anomaly (his value is more than double as high as anybody elses) in terms of "highest amount of hard rounds played in a row that were won per player (for the first 35 rounds)".

Given that I had previously discussed that "effort preference" is a bad marker for ME/CFS as it cannot seperate ME from HV (half of ME patients sitting above the HV "effort preference" mean and half of HV sitting below the ME/CFS "effort preference" mean) I looked at whether this was the case again for "highest amount of hard rounds played in a row that were won per player". It seems to provide a bit of a better seperation than "effort preference" does in the sense that now only 1/3 of ME patients are sitting close to the HV mean (4 ME are above the HV mean and one sits just below), however once again a lot of HV behave exactly as ME patients in the sense that 8 HV patients have a highest amount of hard rounds completed in a row number of 2, so half of HV patients are below 2.3 (which isn’t good to separate the 2 clusters), so once again the seperation isn't too strong and naturally one would expect the separation offered by "hard rounds completed in a row number" to be better than just "effort preference" because to some small degree "hard rounds completed in a row number" is a combination of "successful completion percentage on hard tasks" and "effort preference" and we already know that "successful completion percentage on hard tasks" has a large descrepancy between both groups.

Given those results I asked myself whether something like "highest amount of hard rounds won in a row" would be a good predicitor of "effort preference" or whether the opposite was the case, i.e." effort preference" being a good predicitor of "highest amount of hard rounds won in a row". Naturally one would expect a bit of correlation, because it is very reasonable that someone with a higher effort preference is more likely to have won more hard rounds in a row and vice versa.

Overall it seems that in HV “effort preference does somewhat imply max completion in a row number” especially at the highest and lowest numbers (i.e. low effort preference results in low completion number in row and high effort preference results in high completion number in a row). For ME the picture seems a lot more mixed especially around the ME effort preference mean where basically no conclusions can be drawn.

For the reverse direction there doesn’t seem to be a strong correlation between “max completion in a row number implying effort preference” in HV, if an implication does exist it might primarily be driven by someone like HV H, who is an outlier. In ME this max. completion number in a row does not correlate too strongly with effort preference, in particular for people with very low max. completion numbers little can be said about their effort preference which destroys any possible correlations.

Overall I would consider these results to rather be null results than anything else, but this would have to be confirmed by a rigorous statistical analysis.

Next I looked at "effort preference" being a good predicitor of "highest amount of hard rounds won in a row" and vice versa without any labels on participant status (i.e. without looking at the groups ME and HV seperate).

Due to specific averaging effects (for example very low max. succesfully completion numbers in a row didn't correlate well with low effort preference in ME, however in the general population the lowest numbers are all still due to ME patients, but the overall effort preference increases, making this correlation stronger in the overall population) it seems all previous correlations only become stronger when you leave away the labels of patients status.

Overall, I think it could make sense to have a rigorous look at this to see whether separations are created better without labels (HV vs ME/CFS) than with. In this first scenario it is once again an indication and argument that having ME doesn't drive the "effort preference" results, especially because one would expect "effort preference" to correlate with "number of amounts one successfully completes hard in a row".

(I won't be posting what and how I precisely looked at this because it will be far too long for this post and it wasn't a sufficiently rigorous enough analysis, but I think if someone were to make a scatterplot it might be convincing enough that we could have a closer look at this).

 

[Robert 1973]

I wrote to Dr Bertagnolli and Dr Koroshetz expressing my concerns about the NIH study. For what it is worth, here is the reply.

[Moderators, please move or divide it appropriate.]

On 12 Mar 2024, at 17:35, NIH ME-CFS Working Group Questions <NIHME-CFSWorkingGroupQuestions@ninds.nih.gov> wrote:

Dear Mr. Saunders:


Your email to National Institutes of Health (NIH) Director Dr. Monica M. Bertagnolli and Dr. Walter J. Koroshetz, Director of the National Institute of Neurological Disorders and Stroke (NINDS), concerning myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) has been forwarded to this office for reply.


We are sorry to learn that you have been affected by ME/CFS for more than 30 years. You expressed several concerns with the recently published paper, “Deep phenotyping of post-infectious myalgic encephalomyelitis/chronic fatigue syndrome.” Your desire that these concerns be addressed – and that research in this field receives the attention it deserves – is certainly understandable.


The following website was recently established to provide information about the NIH Intramural Study on ME/CFS: https://www.nih.gov/mecfs/nih-intramural-mecfs-study. This portion of the site provides helpful answers to frequently asked questions about the study:https://www.nih.gov/mecfs/nih-intramural-mecfs-study-qa.


You noted that the study had a low number of participants and that it appears to have neglected studying post-exertional malaise (PEM). PEM was a criterion for participation in the study. The Q&A link mentioned above provides information on PEM-related findings. The study was designed to examine a small group of well-defined patients that could be studied in depth. Patients were at NIH for a few weeks which limited the number of people that could be seen by researchers. When COVID-19 complicated the ability to bring in new patients, researchers determined that a sufficient number of patients had been studied and moved on to analyzing the data.


You also expressed concern that the use of the term “effort preference” would give the impression that people with ME/CFS need to “try harder” and that it would further stigmatize the disease. We understand your concerns and would like to explain this term and how it is used in the context of the Nature Communications article. In our day-to-day lives, the brain must decide how to expend its focus and energy on the tasks that are presented to it. The expenditure of energy is interpreted by the brain as effort. Not all tasks require the same amount of effort, with some tasks being easier and others harder. Tasks are also not equally valuable, with some tasks having more reward and others less. Effort preference is a measurement of the decisions the brain makes of how to utilize its energy based on difficulty and value of a task. We are often not aware that these processes are happening.


In this study, a series of tasks were given in which people with post-infectious (PI) ME/CFS and healthy volunteers had to choose between doing an easy or hard pushing task. The tasks were repeated many times, with different reward values assigned for successful completion. Persons with PI-ME/CFS were more likely to choose the easy task over the hard task compared to the healthy volunteers. This difference in task choice was not influenced by the number of tasks they performed or the value of the tasks. All the factors that did influence the choices are not known, and, as is the usual case, many are not conscious.


The full biological explanation for the observed difference in effort preference in PI-ME/CFS is not known. However, in the study, effort preference was related to differences in the brain, including decrease in catechol neurotransmitters and decreased activation of the right temporo-parietal junction, which plays a role in evaluating and initiating physical action. Therefore, the term does not describe a psychological difference in people with ME/CFS and people without ME/CFS; it describes an actual abnormal finding in how the body’s neural system is supposed to function. Further analysis of the relationship between effort preference and these biological observations is planned.


You also wrote that you hope NIH will invest in high-quality research to develop diagnostic tests and effective treatments. As you may know, NIH research is investigator-initiated. However, we would like to take this opportunity to provide information about the ways that NIH strives to increase quality research on this disease. In 2015, then-NIH Director Dr. Francis S. Collins announced renewed actions to advance ME/CFS research and asked NINDS and the National Institute of Allergy and Infectious Diseases to take the lead. Since then, 20 NIH Institutes, Centers, and Offices have coordinated ME/CFS research through the Trans-NIH ME/CFS Working Group. NIH and the Centers for Disease Control and Prevention also lead an ME/CFS Interagency Collaborative to foster interagency and stakeholder collaboration and communication. You can sign up for the Trans-NIH ME/CFS Working Group listserv by visiting the website (https://www.nih.gov/mecfs) and clicking on the “Join our listserv” icon on the right side of the page. The site also provides information about upcoming events and offers recordings of past events (https://www.nih.gov/mecfs/events).


NINDS also launched an effort to develop a Research Roadmap for ME/CFS, which will identify research priorities to move the field toward translational studies and clinical trials. The Research Roadmap site is at https://www.ninds.nih.gov/about-nin...l/nandsc-mecfs-research-roadmap-working-group. Eight Research Roadmap webinars were completed between August 2023 and January 2024. During this time, the Research Roadmap Working Group developed research priorities for each of the chosen webinar topic areas, as well as cross-cutting research priorities. These research priorities are available on IdeaScale for comment from the community:https://ninds.ideascalegov.com/c/campaigns/1286/about. The recommendations will be reported at the NINDS Advisory Council meeting on May 15 during the open session. The Trans-NIH ME/CFS Working Group is already discussing next steps and how to move the research forward after the report is approved by the Council. They are also discussing how NIH can partner with patient advocacy groups to support research in the future. Research priorities will also be the focus of the next ME/CFS conference in the United Kingdom (organized by Invest in ME) with the idea that we will work collaboratively with the European ME/CFS Research Network to address research priorities going forward. The Roadmap was recently discussed during the Trans-NIH ME/CFS Working Group Advocacy Call on March 4th. A recording and transcript will be available soon athttps://www.nih.gov/mecfs/events.


NIH supported three ME/CFS Collaborative Research Centers at Columbia, Cornell, and Jackson Laboratories as well as a Data Management Coordinating Center (DMCC) at RTI International for 5 years and issued RFAs to support Centers and a DMCC for another 5 years. Information and updates about the ongoing ME/CFS Centers can be found here: https://mecfs.rti.org/. Webinars from each of the Centers and the DMCC provide overviews of their research:https://www.youtube.com/playlist?list=PLJY2toEjWadPflbHSNYyozKcOlC4HzIcQ. In addition, the Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Research Network (MECFSnet) has published two newsletters featuring research news and new and ongoing activities at NIH related to ME/CFS. The newsletters are available at https://mecfs.rti.org/newsletter/.


On December 11, NIH hosted the “Symposium For Promoting The Advancement Of Research Knowledge In ME/CFS” (SPARK ME,https://event.roseliassociates.com/me-cfs-symposium/), a workshop for young/early career investigators. This meeting had 100 individuals participating either in person or via Zoom, including high school students, undergraduate and graduate students, postdoctoral fellows, and early career faculty (assistant and research assistant professors). Participants were from the United States, United Kingdom, Norway, South Africa, Spain, Germany, and Australia, and NIH provided travel awards to 20 individuals. Participants shared oral presentations and posters throughout the workshop and the 2-day NIH conference that followed. There are plans for ongoing communication, collaboration, and networking of the participants and partnering with the Young European ME Research Group (EMERG) in the United Kingdom.


Finally, on December 12-13, NIH hosted a conference called “Advancing ME/CFS Research: Identifying Targets for Intervention and Learning from Long COVID.” More than 1,000 people registered to participate with around 150 in-person participants. Approximately 500 participants joined via the NIH webcast for each session. The presentations provided updates on the state of ME/CFS research with a look toward moving research to translation and clinical trials. Several people with lived experience spoke during the conference and provided very poignant talks about their experiences having ME/CFS and how it has impacted their lives. You can view the videocasts at https://videocast.nih.gov/watch=52631 and https://videocast.nih.gov/watch=52738.


We hope this information is helpful.


Office of Neuroscience Communications and Engagement

National Institute of Neurological Disorders and Stroke

on behalf of the Trans-NIH ME/CFS Working Group


​

 

[EndME]

Yes good point. Perhaps it's worth a try to add the actual completion rates to the model, not just having a +90% completion rate. Maybe that results in a clearer correlation.

Completion rates of hard tasks alone (without being in any model) very clearly offers a better separation in terms of ME vs HV than the effort preference means do (there's only 4 HVs that don't have a hard task completion rate of 100%, whilst 10 ME patients have a hard task completion rate of below 100% and these percentages do scale somewhat, so if you look at completion rate below 60% you get a "marker" with 100% specificity but only 40% sensitivity for ME), however that's primarily due to the fact that effort preference provides essentially no separation of the groups (half of ME patients have an effort preference around the HV mean), rather than hard tasks completion rates telling us much (after all there's sufficiently many pwME who have seemingly no problem completing hard tasks). However, it's rather hard to see clear correlations in the data, which is precisely why the authors decided to construct an arbitrary argument around one barely statistically significant measurement within a pool of hundreds of different measurements.

If not, then I think the explanation is that many patients kept trying on the hard task, despite repeated failure (so the opposite of their view that ME/CFS patients have lower effort preferences). The tasks were much harder for ME/CFS patients (resulting in a large difference in completion rate) but the difference in hard task choices was relatively small because patients compensated by being more motivated, more willing to try, more willing to spend effort etc. And that weakened the correlation between the two. That would be my guess.

In the paper "effort preference" purely refers to percentage of hard tasks chosen (rather than choosing hard despite failure, even though that of course makes little sense overall and also doesn't agree with their press releases where Walitt has said “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”, because clearly there isn't a mismatch, as they can perform less and choose hard less, but I think we have to stick to what the paper says rather than what was said in press releases). Currently I think it might be hard to construct arguments around the other explanations you proposed because thus far we haven't seen much data to strengthen these ideas, because all the different differences between ME and HV seems to be driven by outliers rather than anything consistent, which is why the results are so "wishy-washy" to begin with. For example I find it very hard to conclude anything from this data about the motivation of participants and that is also what I would expect with data from a seemingly unrobust experiment where outliers plays a large role when the sample size is this small.

I fear any hypothetical (rather than evidence based) argument on why "effort preference" might be occuring will only strengthen their position and reinforce the position that it's significant and is happening, when in fact there is almost no evidence to suggest it plays any role to begin with, it offers the same separation a coin flip does and we might be able to come up with data that shows much stronger correlations than what their argument was based around or that their conclusions aren't consistent with the literature or if we point to other inconsistencies.

 

[ME/CFS Skeptic]

Some more data on the correlation between hard task choices and successful completion rates.


I found a value of r= 0.12, that is not significant with this sample size.



Patient D, H and A constitute the 3 dots at the bottom of the graph with low successful completion rates and a large proportion of hard trials. They are the patients that had the many high red bars and kept trying to complete hard tasks despite repeated failure.

 

[EndME]

Something that we haven't looked at yet (mainly because it's harder to do) is that thus far we've only looked at things such as percentage of total hard tasks completed vs percentage of hard tasks chosen, however that doesn't really reflect the nature of the game very well.

I believe a more meaningful analysis would have to look at what role a percentage of previously successfully completed hard trials plays in choosing a hard trial in the next round and so forth, i.e. we've only looked at the overall successful completion percentages on hard tasks once the game is over and how this relates to different things (proportion of hard tasks, maximum amount of successful trials in a row, etc.) however the game is played round by round, so it's more meaningful to see what a round by round or Markovian type assessment yields, rather than assuming that participants know their end-game successful completion rate on hard tasks, which is knowledge they don’t have. For such an analysis it might make sense to me to include the percentages from the practice rounds and using some discounting factor for previous rounds or some Markovian ideas as well as using a cut-off at round 35.

For someone with a 100% completion rate (which is more than half of the participants) or someone with a 0% completion rate (PI-ME/CFS H) this kind of analysis will make 0 difference, but it may make a difference for some inbetweeners.

However, given that the all results of the study are largely driven by the groups of people who have either 100% completion or extremely low completion rates, I expect the results of what had already been discussed on the forum to not change, but it might be worth the effort to have a look at this (perhaps it does push a barely significant value into insignificance or vice versa), or at least it might make for a more rigorous analysis.

 

[EndME]

Some more data on the correlation between hard task choices and successful completion rates.
View attachment 21437

I found a value of r= 0.12, that is not significant with this sample size.

View attachment 21436

Patient D, H and A constitute the 3 dots at the bottom of the graph with low successful completion rates and a large proportion of hard trials. They are the patients that had the many high red bars and kept trying to complete hard tasks despite repeated failure.

I think you'll want to look at the successful completion rates on hard tasks, rather than all tasks, as the easy tasks anyways have a 100% completion rate for everybody (it obviously doesn't make any difference for the analysis above but it looks a bit cleaner to the eye) and possibly also use a cut-off at 35 rounds (w/o practice rounds), at least that's what I found most reasonable.

However, even then you will also find that the correlation is not significant (there's lots of data in this thread on that this is the case and why this is the case) but essentially ME/CFS patients D, H and HV A will destroy any more obvious correlations w.r.t. to this (and similarly there's always outliers w.r.t to other things we've looked at like SF36, max. number of hard trials in a row, etc).

 

[Sam Carter]

... Given that I had previously discussed that "effort preference" is a bad marker for ME/CFS as it cannot seperate ME from HV (half of ME patients sitting above the HV "effort preference" mean and half of HV sitting below the ME/CFS "effort preference" mean) ...

Isn't this the key rebuttal? As in, if the effort preference of a good chunk of ME patients is no different to the healthies (and in many cases exceeds them), then it can't be a central, defining feature of ME.

And if Walitt wants to argue that low effort preference eventually leads to deconditioning, then why haven't the healthy volunteers with low effort preference become deconditioned and developed an ME-like syndrome?

I think there also has to be some question about how robust the test is to confounding factors. Does it really capture the rarefied and intangible concept of effort preference, or is it just a proxy for feeling lousy and under-slept, of having travelled long distances, of being overwhelmed by all the testing, of knowing that the future of ME/CFS research might rest on which button you press in a parlour game that you only half understand.

 

[EndME]

Isn't this the key rebuttal? As in, if the effort preference of a good chunk of ME patients is no different to the healthies (and in many cases exceeds them), then it can't be a central, defining feature of ME.

I think it would be one part of the rebuttal, but only one part of the many parts different brilliant users have already discussed here. One shouldn't forget that the authors don't claim any seperation or anything of that sort, they simply run the GEE analysis (which is a lot more involved than something like a t-test and makes a more intricate analysis possible).

And if Walitt wants to argue that low effort preference eventually leads to deconditioning, then why haven't the healthy volunteers with low effort preference become deconditioned and developed an ME-like syndrome?

They don't argue this (at least not in the paper), so there's no contradiction there. They more just put their spin on their findings, for Walitt that seems to mean that some BPS notion is causing "effort preference" whilst for Nath it seems to mean that some non-identifiable antigen causes some brain dysfunction that results in a different "effort preference".

 

[MSEsperanza]

Thank you to everybody looking in detail at the paper. The statistics and other mathematical details are beyond me. Only able to skim anyway so apologies for not being able to comment on that.

Others' comments look like a very impressive analysis so far -- just am not able to follow.

I still wonder how the investigators can both acknowledge that PEM is a cardinal symptom of ME/CFS and leave it completely aside in the investigations on which they report in what seems to be their main paper?

You noted that the study had a low number of participants and that it appears to have neglected studying post-exertional malaise (PEM). PEM was a criterion for participation in the study. The Q&A link mentioned above provides information on PEM-related findings. The study was designed to examine a small group of well-defined patients that could be studied in depth.

So NIH investigators published two papers on PEM elewehere and refer to these in their Nature Comms paper but only to reassure people that the inclusion criteria demanded PEM -- whereas the very paper that presents their main findings/ main hypothesis is about investigations that didn't take into account PEM in any way?


Edit to add and again edited to fix links to forum discussion on the two PEM papers:

Focus group paper here.

Paper on how they (tried to) measure PEM here.

 

[Sam Carter]

... And if Walitt wants to argue that low effort preference eventually leads to deconditioning, then why haven't the healthy volunteers with low effort preference become deconditioned and developed an ME-like syndrome? ...

They don't argue this (at least not in the paper), so there's no contradiction there. ..

In the paper they write: "Both the autonomic and central motor dysfunction result in a reduction in physical activity. With time, the reduction in physical activity leads to muscular and cardiovascular deconditioning, and functional disability."

It's the trailing "and functional disability" in the sentence that troubles me, as though there is no disability prior to the deconditioning, and that the disability is "functional" (whatever that means). Had they written "and further disability" it would have removed some of the ambiguity. But why include it in the first place? It must occur in other energy or mobility limiting condition like Parkinson's or MS, yet it surely wouldn't merit inclusion in deep phenotyping studies of those conditions?

 

[EndME]

In the paper they write: "Both the autonomic and central motor dysfunction result in a reduction in physical activity. With time, the reduction in physical activity leads to muscular and cardiovascular deconditioning, and functional disability."

It's the trailing "and functional disability" in the sentence that troubles me, as though there is no disability prior to the deconditioning, and that the disability is "functional" (whatever that means). Had they written "and further disability" it would have removed some of the ambiguity. But why include it in the first place? It must occur in other energy or mobility limiting condition like Parkinson's or MS, yet it surely wouldn't merit inclusion in deep phenotyping studies of those conditions?

That indeed seems like a very fair point to me and I stand corrected. It's hard for me to understand what they really mean with these sentences because it just seems to be about some made up TPJ story and drawing arbitrary connections which are not supported by any data. I'm also not sure what "with time" is supposed to mean. Are they not aware that many patients experience a disability that has an extremely sudden onset (in particular in the post-viral cohort they decided to study), rather than anything progressive?

I think the argument that they can make is that, that final abstract is anyways just hypothesis rather than being evidence based, so they feel ok with writing whatever they want.

I think the conclusions they try to draw between the different parts of the study and the EEfRT don't seem to not be based on the available evidence and are equally questionable to everything that has been discussed here, but we haven't really gotten to discussing that yet, since discussing the EEfRT alone already lead to this overly lengthy thread.

 

[Sean]

Therefore, the term does not describe a psychological difference in people with ME/CFS and people without ME/CFS; it describes an actual abnormal finding in how the body’s neural system is supposed to function.

Again, is it because there is a problem with the neural system itself, or with what it is being asked to do? They are fundamentally different phenomenon.

It must occur in other energy or mobility limiting condition like Parkinson's or MS, yet it surely wouldn't merit inclusion in deep phenotyping studies of those conditions?

Give them time, they are working towards making it part of the general psychosomatic model, to be applied to [checks notes] everything.

 

[Hubris]

How can you claim to take PEM seriously, and then come out saying the Hallmark of the illness is that patients don't want to do things and propose some brain imbalance is causing this behavior.

If you believed PEM was real you would naturally just say this is a normal adaptation to the illness. Anyone supporting this view is a closeted BPSer.