Short-Term Effect of Aerobic Exercise on Symptoms in Multiple Sclerosis and Chronic Fatigue Syndrome

[MeSci]

This study was funded by the National Health Service Ayrshire and Arran, Bevan Endowment Fund, Ayrshire and Arran Branch of the Multiple Sclerosis Society, and by a grant from the Medical Development Fund, University of Glasgow.

and an earlier paper by one of the authors


Comparing Two Conditions of Administering the Six-Minute Walk Test in People with Multiple Sclerosis
Brian M. Sandroff, Lara A. Pilutti, Deirdre Dlugonski, Yvonne C. Learmonth, John H. Pula and Robert W. Motl
International Journal of MS Care, Vol. 16, No. 1 (Spring 2014) pp. 48-54
Abstract | Full Text | PDF (649 KB)

Here's a link for that paper.

 

[anciendaze]

I have now decided to read that international journal title as M-scare instead of MS-care.

 

[Little Bluestem]

Some of the standard deviations (SDs) are enormous, aren't they? Stats are my weakest point in science but I know there are some stats whizzes on here.

I didn’t want to say anything and expose my ignorance, but…
Can a standard deviation be greater than the mean where all of the results are positive numbers, as I think the case is here?

 

[anciendaze]

@Little Bluestem

Yes, the SD can be greater than the mean, even when there is a cut-off at zero. The catch is that this cannot be true of a normal (Gaussian) distribution, as I have argued for some time. In a normal distribution, the mean, median and mode are essentially the same, and the only thing you can know about it beyond mean and SD is the number of samples. It contains absolutely no other information.

If this is not true, the obvious inference is that the distribution is not normal, and common parametric statistics do not apply.

I can explain this to some people with mathematical training in terms of limitations on the application of the Central Limit Theorem, but I suspect a group which already has 5 PhDs is incapable of learning, even without the presence of an MD.

All the proofs of which I am aware depend on linear combinations of many distributions, which has a hidden assumption that distributions will combine additively. If distributions combine multiplicatively, as in reliability calculations where a single failure can destroy an entire system, the resulting distribution will not be normal. Lévy distributions are one class of example, and these fail to have a well-defined SD. The SD you compute will be an artifact of the bounds you set and the number of samples. This is not a good prerequisite for ANOVA, unless you are determined to commit a deception, safe in the knowledge that few will go to the trouble to check your hidden assumptions.

 

[osisposis]

J Neuroimmunol. 2010 Jun;223(1-2):124-7. doi: 10.1016/j.jneuroim.2010.03.014. Epub 2010 Apr 20.
Elevated plasma C4a levels in multiple sclerosis correlate with disease activity.
Ingram G1, Hakobyan S, Robertson NP, Morgan BP.
Author information
Abstract

Complement plays a pivotal role in the pathogenesis of multiple sclerosis. C4a, an activated fragment of complement component C4, has been linked to disease activity. We correlated plasma C4 and plasma and CSF C4a with clinical disease in a well-characterised cohort of patients and controls. Plasma C4 was non-significantly and CSF C4a was significantly elevated overall in patients compared to controls. Plasma C4a was raised only in acute relapse, decreasing over 2 months. Results demonstrate intrathecal and systemic activation of complement, reflected in changes in CSF and plasma C4a. The data support a role for complement activation in pathogenesis and suggest a systemic component to the disease.

http://www.ncbi.nlm.nih.gov/pubmed/20409594

 

[osisposis]

Mult Scler. Oct 2012; 18(10): 1401–1411.
doi: 10.1177/1352458512438238
PMCID: PMC3697901
Systemic complement profiling in multiple sclerosis as a biomarker of disease state

Results:

Increased plasma levels of C3 (p<0.003), C4 (p<0.001), C4a (p<0.001), C1 inhibitor (p<0.001), and factor H (p<0.001), and reduced levels of C9 (p<0.001) were observed in MS patients compared with controls. Combined profiling of these analytes produced a statistical model with a predictive value of 97% for MS and 73% for clinical relapse when combined with selected demographic data. CSF-plasma correlations suggested that source of synthesis of these components was both systemic and central.
Conclusion:

These data provide further evidence of alterations in both local and systemic expression and activation of complement in MS and suggest that complement profiling may be informative as a biomarker of MS disease, although further work is needed to determine its use in distinguishing MS from its differential.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3697901/


Acta Neuropathol Commun. 2014; 2(1): 53.
Published online May 9, 2014. doi: 10.1186/2051-5960-2-53
PMCID: PMC4048455
Complement activation in multiple sclerosis plaques: an immunohistochemical analysis

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4048455/