Category: Methodology

Is the International Physical Activity Questionnaire-short form (IPAQ-SF) valid for assessing physical activity in Chronic Fatigue Syndrome?

Abstract:

PURPOSE: To evaluate the criterion validity and internal consistency of the International Physical Activity Questionnaire-short form (IPAQ-sf) in Chronic Fatigue Syndrome (CFS) patients.

METHOD: Fifty-six CFS patients completed the IPAQ-sf after they wore a tri-axial accelerometer and filled out activity diaries during 1 week. Spearman rank correlation coefficients and Cronbach’s Alpha were calculated.

RESULTS: The IPAQ-sf correlated significantly with the energy expenditure and Metabolic Equivalents (METs) minutes spent moderately to vigorously active following the activity diary and accelerometer. These correlation coefficients were however low (r varying between 0.282 and 0.426) and rather irrelevant, since CFS patients hardly reach moderate or vigorous activity levels. Internal consistency between the three subitems used for the total score of the IPAQ-sf was 0.337.

CONCLUSION: The observed associations between the IPAQ-sf data and the data obtained from the accelerometer (gold standard) and the diaries were too low to be in support of the use of the IPAQ-sf in patients with CFS. The IPAQ-sf does not seem an appropriate tool to assess physical activity in CFS patients. Further study is required to seek for a valid, practical and affordable tool.

 

Source: Meeus M, Van Eupen I, Willems J, Kos D, Nijs J. Is the International Physical Activity Questionnaire-short form (IPAQ-SF) valid for assessing physical activity in Chronic Fatigue Syndrome? Disabil Rehabil. 2011;33(1):9-16. doi: 10.3109/09638288.2010.483307. Epub 2010 May 6. https://www.ncbi.nlm.nih.gov/pubmed/20446802

 

Further validation of the Multidimensional Fatigue Inventory in a US adult population sample

Abstract:

BACKGROUND: The Multidimensional Fatigue Inventory (MFI-20) was developed in 1995. Since then, it has been widely used in cancer research and cancer-related illnesses but has never been validated in fatiguing illnesses or in a large US population-selected sample. In this study, we sought to examine the reliability and validity of the MFI-20 in the population of the state of Georgia, USA. Further, we assessed whether the MFI-20 could serve as a complementary diagnostic tool in chronically fatigued and unwell populations.

METHODS: The data derive from a cross-sectional population-based study investigating the prevalence of chronic fatigue syndrome (CFS) in Georgia. The study sample was comprised of three diagnostic groups: CFS-like (292), chronically unwell (269), and well (222). Participants completed the MFI-20 along with several other measures of psychosocial functioning, including the Medical Outcomes Survey Short Form-36 (SF-36), the Zung Self-Rating Depression Scale (SDS), and the Spielberger State-Trait Anxiety Inventory (STAI). We assessed the five MFI-20 subscales using several criteria: inter-item correlations, corrected item-total correlations, internal consistency reliability (Cronbach’s alpha coefficients), construct validity, discriminant (known-group) validity, floor/ceiling effects, and convergent validity through correlations with the SF-36, SDS, and STAI instruments.

RESULTS: Averaged inter-item correlations ranged from 0.38 to 0.61, indicating no item redundancy. Corrected item-total correlations for all MFI-20 subscales were greater than 0.30, and Cronbach’s alpha coefficients achieved an acceptable level of 0.70. No significant floor/ceiling effect was observed. Factor analysis demonstrated factorial complexity. The MFI-20 also distinguished clearly between three diagnostic groups on all subscales. Furthermore, correlations with depression (SDS), anxiety (STAI), and functional impairment (SF-36) demonstrated strong convergent validity.

CONCLUSIONS: This study provides support for the MFI-20 as a valuable tool when used in chronically unwell and well populations. It also suggests that the MFI-20 could serve as a complementary diagnostic tool in fatiguing illnesses, such as CFS.

 

Source: Lin JM, Brimmer DJ, Maloney EM, Nyarko E, Belue R, Reeves WC. Further validation of the Multidimensional Fatigue Inventory in a US adult population sample. Popul Health Metr. 2009 Dec 15;7:18. doi: 10.1186/1478-7954-7-18. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2801470/ (Full article)

 

Autoantibodies to lens epithelium-derived growth factor/transcription co-activator P75 (LEDGF/P75) in children with chronic nonspecific complaints and with positive antinuclear antibodies

Abstract:

Autoimmune fatigue syndrome (AIFS) is characterized by chronic nonspecific complaints, consistently positive antinuclear antibodies (ANA), and lack of alternate medical explanations. A newly recognized antibody, named anti-Sa, was detected in approximately 40% of the patients by Western blot (WB) using HeLa extract.

Some patients with AIFS later develop chronic fatigue syndrome (CFS), and most of them are positive for anti-Sa. On the other hand, Muro et al. reported anti-DFS70 in patients with CFS. Anti-Sa and anti-DFS70 were turned out to be same specificities by exchanging studies of blind sera. The target antigen of anti-DFS70 was identified as lens epithelium derived growth factor/transcription co-activator p75 (LEDGF/p75).

The objectives of this study are to confirm whether the target antigen of anti-Sa is also LEDGF/p75, and to develop ELISA system by using recombinant protein. Recombinant protein of LEDGF/p75 was purchased from Protein One (Bethesda, MD, USA). We developed an ELISA system to detect anti-LEDGF/p75 by coating this recombinant protein. 226 sera of AIFS patients (including 36 CFS patients) were applied to this ELISA assay and Western immunoblot, and it was revealed that anti-Sa-positive sera defined by WB and sera positive for anti-LEDGF/p75 on ELISA were identical.

Moreover, reactivities of anti-Sa on WB were inhibited by pre-incubating with recombinant LEDGF/p75, and eluted antibodies from the nitrocellulose membrane could react on the ELISA. These results confirm that the Sa antigen is LEDGF/p75. The ELISA assay using recombinant LEDGF/p75 could be a promising tool for measuring anti-Sa and consequently for diagnosing CFS.

 

Source: Kuwabara N, Itoh Y, Igarshi T, Fukunaga Y. Autoantibodies to lens epithelium-derived growth factor/transcription co-activator P75 (LEDGF/P75) in children with chronic nonspecific complaints and with positive antinuclear antibodies. Autoimmunity. 2009 Sep;42(6):492-6. Doi: 10.1080/08916930902736663. https://www.ncbi.nlm.nih.gov/pubmed/19657776

 

Clinical assessment of the physical activity pattern of chronic fatigue syndrome patients: a validation of three methods

Abstract:

BACKGROUND: Effective treatment of chronic fatigue syndrome (CFS) with cognitive behavioural therapy (CBT) relies on a correct classification of so called ‘fluctuating active’ versus ‘passive’ patients. For successful treatment with CBT is it especially important to recognise the passive patients and give them a tailored treatment protocol. In the present study it was evaluated whether CFS patient’s physical activity pattern can be assessed most accurately with the ‘Activity Pattern Interview’ (API), the International Physical Activity Questionnaire (IPAQ) or the CFS-Activity Questionnaire (CFS-AQ).

METHODS: The three instruments were validated compared to actometers. Actometers are until now the best and most objective instrument to measure physical activity, but they are too expensive and time consuming for most clinical practice settings. In total 226 CFS patients enrolled for CBT therapy answered the API at intake and filled in the two questionnaires. Directly after intake they wore the actometer for two weeks. Based on receiver operating characteristic (ROC) curves the validity of the three methods were assessed and compared.

RESULTS: Both the API and the two questionnaires had an acceptable validity (0.64 to 0.71). None of the three instruments was significantly better than the others. The proportion of false predictions was rather high for all three instrument. The IPAQ had the highest proportion of correct passive predictions (sensitivity 70.1%).

CONCLUSION: The validity of all three instruments appeared to be fair, and all showed rather high proportions of false classifications. Hence in fact none of the tested instruments could really be called satisfactory. Because the IPAQ showed to be the best in correctly predicting ‘passive’ CFS patients, which is most essentially related to treatment results, it was concluded that the IPAQ is the preferable alternative for an actometer when treating CFS patients in clinical practice.

 

Source: Scheeres K, Knoop H, Meer vd, Bleijenberg G. Clinical assessment of the physical activity pattern of chronic fatigue syndrome patients: a validation of three methods. Health Qual Life Outcomes. 2009 Apr 1;7:29. doi: 10.1186/1477-7525-7-29. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2674446/ (Full article)

 

Validation of the energy index point score to serially measure the degree of disability in patients with chronic fatigue syndrome

Abstract:

BACKGROUND: A simple quantitative accurate method for assessing the degree of fatigue in patients with chronic fatigue syndrome (CFS) is necessary for physicians and patients. Severity of the disease and recovery can, thus, be assayed.

PATIENT AND METHODS: From February 1-27, 2007, fifty-six consecutive CFS patients at a single treatment center were simultaneously evaluated by the patient with the fatigue severity score (FSS), and by consensus of both patient and physician by the energy index (EI) point score.

RESULTS: The FSS and EI correlated well, 0.67, p<0.001.

CONCLUSION: The El point score is a validated reliable method to assess fatigue in CFS patients.

 

Source: Lerner AM, Beqaj SH, Fitzgerald JT. Validation of the energy index point score to serially measure the degree of disability in patients with chronic fatigue syndrome. In Vivo. 2008 Nov-Dec;22(6):799-801. http://iv.iiarjournals.org/content/22/6/799.long (Full article)

 

A Bayesian approach to gene-gene and gene-environment interactions in chronic fatigue syndrome

Abstract:

INTRODUCTION: In the study of genomics, it is essential to address gene-gene and gene-environment interactions for describing the complex traits that involves disease-related mechanisms. In this work, our goal is to detect gene-gene and gene-environment interactions resulting from the analysis of chronic fatigue syndrome patients’ genetic and demographic factors including SNPs, age, gender and BMI.

MATERIALS & METHODS: We employed the dataset that was original to the previous study by the Centers for Disease Control and Prevention Chronic Fatigue Syndrome Research Group. To investigate gene-gene and gene-environment interactions, we implemented a Bayesian based method for identifying significant interactions between factors. Here, we employed a two-stage Bayesian variable selection methodology based on Markov Chain Monte Carlo approaches.

RESULTS: By applying our Bayesian based approach, NR3C1 was found in the significant two-locus gene-gene effect model, as well as in the significant two-factor gene-environment effect model. Furthermore, a significant gene-environment interaction was identified between NR3C1 and gender. These results support the hypothesis that NR3C1 and gender may play a role in biological mechanisms associated with chronic fatigue syndrome.

CONCLUSION: We demonstrated that our Bayesian based approach is a promising method to assess the gene-gene and gene-environment interactions in chronic fatigue syndrome patients by using genetic factors, such as SNPs, and demographic factors such as age, gender and BMI.

 

Source: Lin E, Hsu SY. A Bayesian approach to gene-gene and gene-environment interactions in chronic fatigue syndrome. Pharmacogenomics. 2009 Jan;10(1):35-42. Doi: 10.2217/14622416.10.1.35. https://www.ncbi.nlm.nih.gov/pubmed/19102713

 

Assessment of fibromyalgia & chronic fatigue syndrome: a new protocol designed to determine work capability–chronic pain abilities determination (CPAD)

Abstract:

The objective was to design a protocol to assess work ability in people suffering ill-defined painful and disabling disorders, the outstanding prototype of which is fibromyalgia/chronic fatigue syndrome (FM/CSF).Following an extensive literature search, the mos appropriate components of current methods of assessment of physical and cognitive abilities were incorporated into the protocol, occasionally with appropriate modification to suit the specific requirements of the individual.

The initial part of the assessment consists of a standard history taking, principally focusing on the patient’s self-reported physical and cognitive abilities and disabilities, as well as the completion of established pain and fatigue scales, and relevant disability questionnaires.

Following this, physical and cognitive abilities are objectively assessed on two separate occasions, utilizing computerized hand-held dynamometers, inclinometers, algometers, and force dynamometers. Specific work simulation tests using the industrial standards Methods-Time-Measurement testing are availed of, as is aerobic testing using the Canadian Aerobic Fitness Test (CAFT). Objective computerised neuro-cognitive testing are also utilised as an integral component of the assessment. All results are then subject to specific computerized analysis and compared to normative and standardised work-based databases.

The designed system produces reliable, consistent and reproducible results. It also proves capable of detecting any inconsistencies in patient input and results, in addition to being independent of any possible assessor bias. A new protocol has been designed to determine the working capability of individuals who suffer from various chronic disabling conditions, and represents a significant step forward in a difficult but rapidly expanding area of medical practice.

 

Source: Kelly M, Gagne R, Newman JD, Olney C, Gualtieri C, Trail D. Assessment of fibromyalgia & chronic fatigue syndrome: a new protocol designed to determine work capability–chronic pain abilities determination (CPAD). Ir Med J. 2008 Oct;101(9):277-8. https://www.ncbi.nlm.nih.gov/pubmed/19051616

 

Integrated weighted gene co-expression network analysis with an application to chronic fatigue syndrome

Abstract:

BACKGROUND: Systems biologic approaches such as Weighted Gene Co-expression Network Analysis (WGCNA) can effectively integrate gene expression and trait data to identify pathways and candidate biomarkers. Here we show that the additional inclusion of genetic marker data allows one to characterize network relationships as causal or reactive in a chronic fatigue syndrome (CFS) data set.

RESULTS: We combine WGCNA with genetic marker data to identify a disease-related pathway and its causal drivers, an analysis which we refer to as “Integrated WGCNA” or IWGCNA. Specifically, we present the following IWGCNA approach: 1) construct a co-expression network, 2) identify trait-related modules within the network, 3) use a trait-related genetic marker to prioritize genes within the module, 4) apply an integrated gene screening strategy to identify candidate genes and 5) carry out causality testing to verify and/or prioritize results. By applying this strategy to a CFS data set consisting of microarray, SNP and clinical trait data, we identify a module of 299 highly correlated genes that is associated with CFS severity. Our integrated gene screening strategy results in 20 candidate genes. We show that our approach yields biologically interesting genes that function in the same pathway and are causal drivers for their parent module. We use a separate data set to replicate findings and use Ingenuity Pathways Analysis software to functionally annotate the candidate gene pathways.

CONCLUSION: We show how WGCNA can be combined with genetic marker data to identify disease-related pathways and the causal drivers within them. The systems genetics approach described here can easily be used to generate testable genetic hypotheses in other complex disease studies.

 

Source: Presson AP, Sobel EM, Papp JC, Suarez CJ, Whistler T, Rajeevan MS, Vernon SD, Horvath S. Integrated weighted gene co-expression network analysis with an application to chronic fatigue syndrome.BMC Syst Biol. 2008 Nov 6;2:95. doi: 10.1186/1752-0509-2-95. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2625353/ (Full article)

 

Bayesian biomarker identification based on marker-expression proteomics data

Abstract:

We are studying variable selection in multiple regression models in which molecular markers and/or gene-expression measurements as well as intensity measurements from protein spectra serve as predictors for the outcome variable (i.e., trait or disease state).

Finding genetic biomarkers and searching genetic-epidemiological factors can be formulated as a statistical problem of variable selection, in which, from a large set of candidates, a small number of trait-associated predictors are identified. We illustrate our approach by analyzing the data available for chronic fatigue syndrome (CFS).

CFS is a complex disease from several aspects, e.g., it is difficult to diagnose and difficult to quantify. To identify biomarkers we used microarray data and SELDI-TOF-based proteomics data. We also analyzed genetic marker information for a large number of SNPs for an overlapping set of individuals. The objectives of the analyses were to identify markers specific to fatigue that are also possibly exclusive to CFS. The use of such models can be motivated, for example, by the search for new biomarkers for the diagnosis and prognosis of cancer and measures of response to therapy. Generally, for this we use Bayesian hierarchical modeling and Markov Chain Monte Carlo computation.

 

Source: Bhattacharjee M, Botting CH, Sillanpää MJ. Bayesian biomarker identification based on marker-expression proteomics data. Genomics. 2008 Dec;92(6):384-92. doi: 10.1016/j.ygeno.2008.06.006. Epub 2008 Aug 15. http://www.sciencedirect.com/science/article/pii/S0888754308001420 (Full article)

 

Teaching medical students about medically unexplained illnesses: a preliminary study

Abstract:

BACKGROUND: This study examined how an interactive seminar focusing on two medically unexplained illnesses, chronic fatigue syndrome (CFS) and fibromyalgia, influenced medical student attitudes toward CFS, a more strongly stigmatized illness.

METHODS: Forty-five fourth year medical students attended a 90 minute interactive seminar on the management of medically unexplained illnesses that was exemplified with CFS and fibromyalgia. A modified version of the CFS attitudes test was administered immediately before and after the seminar.

RESULTS: Pre-seminar assessment revealed neutral to slightly favorable toward CFS. At the end of the seminar, significantly more favorable attitudes were found toward CFS in general (t (42) = 2.77; P < 0.01) and for specific items that focused on (1) supporting more CFS research funding (t (42) = 4.32; P < 0.001; (2) employers providing flexible hours for people with CFS (t (42) = 3.52, P < 0.01); and (3) viewing CFS as not primarily a psychological disorder (t (42) = 2.87, P < 0.01). Thus, a relatively brief exposure to factual information on specific medically unexplained illnesses was associated with more favorable attitudes toward CFS in fourth year medical students.

CONCLUSION: This type of instruction may lead to potentially more receptive professional attitudes toward providing care to these underserved patients.

 

Source: Friedberg F, Sohl SJ, Halperin PJ. Teaching medical students about medically unexplained illnesses: a preliminary study. Med Teach. 2008;30(6):618-21. doi: 10.1080/01421590801946970. https://www.ncbi.nlm.nih.gov/pubmed/18608944