Diagnosis – Page 10 – American ME and CFS Society

Cytokine expression profiles of immune imbalance in post-mononucleosis chronic fatigue

Abstract:

BACKGROUND: As Chronic Fatigue Syndrome (CFS) has been known to follow Epstein-Bar virus (EBV) and other systemic infections; our objective was to describe differences in immune activation in post-infective CFS (PI-CFS) patients and recovered controls. We studied 301 adolescents prospectively over 24 months following the diagnosis of monospot-positive infectious mononucleosis (IM). We found an incidence of CFS at 6, 12 and 24 months of 13%, 7% and 4% respectively.

METHODS: Using chemiluminescent imaging we measured the concentrations of IL-1a, 1b, 2, 4, 5, 6, 8, 10, 12 (p70), 13, 15, 17 and 23, IFN-γ, TNF-α and TNF-β in duplicate plasma samples available in bio-bank from 9 PI-CFS subjects and 12 recovered controls at 24 months post-infection.

RESULTS: Standard comparative analysis indicated significant differences in IL-8 and 23 across subject groups. In constructing a linear classification model IL-6, 8 and 23 were selected by two different statistical approaches as discriminating features, with IL-1a, IL-2 and IFN-γ also selected in one model or the other. This supported an assignment accuracy of better than 80% at a confidence level of 0.95 into PI-CFS versus recovered controls.

CONCLUSION: These results suggest that co-expression patterns in as few as 5 cytokines associated with Th17 function may hold promise as a tool for the diagnosis of post-infectious CFS.

Source: Broderick G, Katz BZ, Fernandes H, Fletcher MA, Klimas N, Smith FA, O’Gorman MR, Vernon SD, Taylor R. Cytokine expression profiles of immune imbalance in post-mononucleosis chronic fatigue. J Transl Med. 2012 Sep 13;10:191. doi: 10.1186/1479-5876-10-191. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3480896/ (Full article)

Visible and near-infrared spectra collected from the thumbs of patients with chronic fatigue syndrome for diagnosis

Abstract:

BACKGROUND: Currently, diagnosis of chronic fatigue syndrome (CFS) is based on clinical symptoms and therefore relies on the experience and skill of the doctors. Here, we have examined the possible diagnosis of CFS based on spectral information and chemometrics analysis, such as principal component analysis (PCA) and soft modeling of class analogy (SIMCA).

METHODS: Visible and near-infrared (Vis-NIR) spectroscopy was used to examine possible changes in the region of 600-1100 nm in thumbs and assessed.

RESULTS: The Vis-NIR spectra of thumbs from 57 CFS patients and 74 healthy volunteers were subjected to PCA and SIMCA to develop multivariate models to discriminate between CFS patients and healthy individuals. The model was further assessed by the prediction of 120 determinations (60 in the healthy group and 60 in the CFS patient group). The PCA model predicted a discrimination of the masked samples; specifically the SIMCA model correctly predicted 51 of 60 (83.3%) healthy volunteers and 42 of 60 (70%) CFS patients.

CONCLUSIONS: Despite the relatively small number of subjects involved in this trial, who were exclusively Japanese, our results imply that Vis-NIR spectroscopy of the thumb combined with chemometrics analysis may provide a valuable tool for diagnosing CFS.

Source: Sakudo A, Kuratsune H, Kato YH, Ikuta K. Visible and near-infrared spectra collected from the thumbs of patients with chronic fatigue syndrome for diagnosis. Clin Chim Acta. 2012 Oct 9;413(19-20):1629-32. doi: 10.1016/j.cca.2012.05.004. Epub 2012 May 11. https://www.ncbi.nlm.nih.gov/pubmed/22583968

Alternative diagnoses to chronic fatigue syndrome in referrals to a specialist service: service evaluation survey

Abstract:

OBJECTIVE: To assess the accuracy of diagnoses made by referrers to a chronic fatigue syndrome (CFS) service.

DESIGN: Retrospective service evaluation surveys of both rejected referral letters and medical case-notes after full clinical assessment.

SETTING: A specialist CFS clinic in London, UK.

PARTICIPANTS: In the first survey, we assessed rejected referral letters between March 2007 and September 2008. In the second survey, we ascertained the primary diagnosis made in case-notes of 250 consecutive new patients assessed between April 2007 and November 2008.

MAIN OUTCOME MEASURES: Reasons for rejection of referrals and primary diagnosis in those assessed.

RESULTS: In the first survey, 154 out of 418 referrals (37%) were rejected. Of these, 77 out of the available 127 referrals (61%) had a likely alternative diagnosis. In the second survey of clinically assessed patients, 107 (43%) had alternative medical/psychiatric diagnoses, while 137 out of 250 (54%) patients received a diagnosis of CFS. The commonest alternative medical diagnoses of those assessed were sleep disorders and the commonest alternative psychiatric diagnosis was depressive illness. Altogether 184 of 377 (49%) patients had alternative diagnoses to CFS.

CONCLUSIONS: Half of all the referred patients to a specialist CFS clinic had alternative medical and psychiatric diagnoses. Specialist medical assessment for patients with unexplained, disabling, chronic fatigue needs to incorporate both medical and psychiatric assessments.

Source: Devasahayam A, Lawn T, Murphy M, White PD. Alternative diagnoses to chronic fatigue syndrome in referrals to a specialist service: service evaluation survey. JRSM Short Rep. 2012 Jan;3(1):4. doi: 10.1258/shorts.2011.011127. Epub 2012 Jan 12.https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3269106/ (Full article)

Chronic Fatigue Syndrome/Myalgic Encephalomyelitis (or Encephalopathy): Diagnosis and Management of Chronic Fatigue Syndrome/Myalgic Encephalomyelitis (or Encephalopathy) in Adults and Children [Internet]

Excerpt:

The guideline covers care provided by healthcare professionals who have direct contact with and make decisions about the care of people with chronic fatigue syndrome/myalgic encephalomyelitis (or encephalopathy) (CFS/ME). It covers care provided in primary and secondary care, and in specialist centres/teams. The Guideline Development Group (GDG) developed this guideline with the aims of: increasing the recognition of CFS/ME; influencing practice in the ‘real world’; improving access to appropriate services, and supporting consistent service provision; emphasising the need for multidisciplinary working; improving care for patients, particularly for those with severe CFS/ME; providing guidance on ‘best practice’ for children with CFS/ME; balancing clinical guidance with flexibility and management tailored to the needs of the patient; facilitating communication between practitioners and patients, and their families or carers, as appropriate.

Source: National Collaborating Centre for Primary Care (UK). London: Royal College of General Practitioners (UK); 2007 Aug. National Institute for Health and Clinical Excellence: Guidance. Chronic Fatigue Syndrome/Myalgic Encephalomyelitis (or Encephalopathy): Diagnosis and Management of Chronic Fatigue Syndrome/Myalgic Encephalomyelitis (or Encephalopathy) in Adults and Children [Internet]. https://www.ncbi.nlm.nih.gov/pubmedhealth/PMH0009713/ (Full document)

Diagnostic accuracy of symptoms characterising chronic fatigue syndrome

Abstract:

PURPOSE: To determine the diagnostic accuracy for single symptoms and clusters of symptoms to distinguish between individuals with and without chronic fatigue syndrome (CFS).

METHODS: A cohort study was conducted in an exercise physiology laboratory in an academic setting. Thirty subjects participated in this study (n = 16 individuals with CFS; n = 14 non-disabled sedentary matched control subjects). An open-ended symptom questionnaire was administered 1 week following the second of two maximal cardiopulmonary exercise tests administered 24 h apart.

RESULTS: Receiver operating characteristics (ROC) curve analysis was significant for failure to recover within 1 day (area under the curve = 0.864, 95% confidence interval [CI]: 0.706-1.00, p = 0.001) but not within 7 days. Clinimetric properties of failure to recover within 1 day to predict membership in the CFS cohort were sensitivity 0.80, specificity 0.93, positive predictive value 0.92, negative predictive value 0.81, positive likelihood ratio 11.4, and negative likelihood ratio 0.22. Fatigue demonstrated high sensitivity and modest specificity to distinguish between cohorts, while neuroendocrine dysfunction, immune dysfunction, pain, and sleep disturbance demonstrated high specificity and modest sensitivity. ROC analysis suggested cut-point of three associated symptoms (0.871, 95% CI: 0.717-1.00, p < 0.001). A significant binary logistic regression model (p < 0.001) revealed immune abnormalities, sleep disturbance and pain accurately classified 92% of individuals with CFS and 88% of control subjects.

CONCLUSIONS: A cluster of associated symptoms distinguishes between individuals with and without CFS. Fewer associated symptoms may be necessary to establish a diagnosis of CFS than currently described.

Source: Davenport TE, Stevens SR, Baroni K, Van Ness M, Snell CR. Diagnostic accuracy of symptoms characterising chronic fatigue syndrome. Disabil Rehabil. 2011;33(19-20):1768-75. doi: 10.3109/09638288.2010.546936. Epub 2011 Jan 6. https://www.ncbi.nlm.nih.gov/pubmed/21208154

Psychiatric misdiagnoses in patients with chronic fatigue syndrome

Abstract:

OBJECTIVES: The aim of this study was to examine the accuracy of doctors at diagnosing co-morbid psychiatric disorders in patients with chronic fatigue syndrome (CFS).

DESIGN: Case series comparing clinical diagnoses with a standardized structured psychiatric interview.

SETTING: Secondary care specialist chronic fatigue syndrome clinic.

PARTICIPANTS: One hundred and thirty-five participants of a randomized controlled trial of non-pharmacological treatments at one centre in the PACE trial.

MAIN OUTCOME MEASURES: Current psychiatric diagnoses made by CFS specialist doctors, compared with current psychiatric diagnoses made independently using a structured psychiatric interview.

RESULTS: Clinicians identified 59 (44%, 95% CI 39-56%) of patients as suffering from a co-morbid psychiatric disorder compared to 76 (56%, CI 53-69%) by structured interview. Depressive and anxiety disorders were most common. Clinicians were twice as likely to miss diagnoses (30 patients, 22%) than misdiagnose them (13, 10%). Psychiatrists were less likely to miss diagnoses than other clinicians, but were as likely to misdiagnose them.

CONCLUSIONS: Doctors assessing patients in a chronic fatigue syndrome clinic miss psychiatric diagnoses more often than misdiagnosing them. Missed diagnoses are common. CFS clinic doctors should be trained to diagnose psychiatric disorders.

Source: Lawn T, Kumar P, Knight B, Sharpe M, White PD. Psychiatric misdiagnoses in patients with chronic fatigue syndrome. JRSM Short Rep. 2010 Sep 6;1(4):28. doi: 10.1258/shorts.2010.010042. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2984352/ (Full article)

Making the diagnosis of Chronic Fatigue Syndrome/Myalgic Encephalitis in primary care: a qualitative study

Abstract:

BACKGROUND: NICE guidelines emphasise the role of the primary care team in the management of patients with Chronic Fatigue Syndrome/Myalgic Encephalitis (CFS/ME). A key stage in effective management is making an accurate early diagnosis, supported by appropriate referral.

METHODS: A nested qualitative study within a multi-centre randomised controlled trial which aimed to explore GPs’ views on their role in making the diagnosis of CFS/ME and subsequent management of patients in primary care. Semi-structured interviews with 22 GPs. Interviews were transcribed verbatim and an iterative approach used to develop themes from the dataset.

RESULTS: GPs described difficulties in defining CFS/ME and suggested that their role in making a diagnosis was to exclude physical causes for the patient’s symptoms, but they reported little confidence in positively attributing the label of CFS/ME to a patient and their symptoms. GPs suggested that the label of CFS/ME could be potentially harmful for the patient. The role of referral to secondary care was debated and GPs struggled defining their own role in management of this group of patients.

CONCLUSIONS: Until GPs feel comfortable making the diagnosis of CFS/ME and facilitating initial management, and have appropriate services to refer patients to, there will continue to be delays in confirming the diagnosis and patients presenting in primary care with fatigue may not receive appropriate care.

TRIAL REGISTRATION: ISRCTN 74156610.

Source: Chew-Graham C, Dowrick C, Wearden A, Richardson V, Peters S. Making the diagnosis of Chronic Fatigue Syndrome/Myalgic Encephalitis in primary care: a qualitative study. BMC Fam Pract. 2010 Feb 23;11:16. doi: 10.1186/1471-2296-11-16. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2836312/ (Full article)

Sleep apnea and psychological functioning in chronic fatigue syndrome

Abstract:

Objectives were to explore: (1) whether sleep apnea/hypopnea syndrome (SAHS) should be considered a chronic fatigue syndrome (CFS) comorbidity, rather than a diagnostic exclusion criterion; and (2) to compare sleep/wake/ psychopathology in individuals with CFS, controls and another illness.

Participants (CFS, SAHS, controls) completed questionnaires and were evaluated for SAHS; 68 percent were subsequently diagnosed with SAHS. CFS participants with and without SAHS did not differ. Both clinical groups were less well adjusted than controls. We conclude that SAHS should not be an exclusion criterion for CFS and that psychological problems in CFS seem a consequence of coping with illness.

Source: Libman E, Creti L, Baltzan M, Rizzo D, Fichten CS, Bailes S. Sleep apnea and psychological functioning in chronic fatigue syndrome. J Health Psychol. 2009 Nov;14(8):1251-67. Doi: 10.1177/1359105309344895. https://www.ncbi.nlm.nih.gov/pubmed/19858344

An evaluation of exclusionary medical/psychiatric conditions in the definition of chronic fatigue syndrome

Abstract:

BACKGROUND: The diagnosis of chronic fatigue syndrome (CFS) in research studies requires the exclusion of subjects with medical and psychiatric conditions that could confound the analysis and interpretation of results. This study compares illness parameters between individuals with CFS who have and those who do not have exclusionary conditions.

METHODS: We used a population-based telephone survey of randomly selected individuals, followed by a clinical evaluation in the study metropolitan, urban, and rural counties of Georgia, USA. The medical and psychiatric histories of the subjects were examined and they underwent physical and psychiatric examinations and laboratory screening. We also employed the multidimensional fatigue inventory (MFI), the medical outcomes survey short form-36 (SF-36) and the US Centres for Disease Control and Prevention symptom inventory (SI).

RESULTS: Twenty-nine percent (1,609) of the 5623 subjects who completed the detailed telephone interview reported exclusionary diagnoses and we diagnosed an exclusionary condition in 36% of 781 clinically evaluated subjects. Both medical and psychiatric exclusionary conditions were more common in women, blacks and participants from rural areas. Subjects with and without exclusions had similar levels of fatigue and impairment as measured by the MFI and SF-36; those with CFS-like illness (not meeting the formal CFS definition) were more likely to have an exclusionary diagnosis. After adjusting for demographics, body mass index, fatigue subscales, SF-36 subscales and CFS symptoms, CFS-like illness did not remain significantly associated with having an exclusionary diagnosis.

CONCLUSION: Medical and psychiatric illnesses associated with fatigue are common among the unwell. Those who fulfill CFS-like criteria need to be evaluated for potentially treatable conditions. Those with exclusionary conditions are equally impaired as those without exclusions.

Comment in: Chronic fatigue syndrome: identifying zebras amongst the horses. [BMC Med. 2009]

Source: Jones JF, Lin JM, Maloney EM, Boneva RS, Nater UM, Unger ER, Reeves WC. An evaluation of exclusionary medical/psychiatric conditions in the definition of chronic fatigue syndrome. BMC Med. 2009 Oct 12;7:57. doi: 10.1186/1741-7015-7-57. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2768736/ (Full article)

Chronic fatigue syndrome: identifying zebras amongst the horses

Abstract:

There are currently no investigative tools or physical signs that can confirm or refute the presence of chronic fatigue syndrome(CFS). As a result, clinicians must decide how long to keep looking for alternative explanations for fatigue before settling on a diagnosis of CFS. Too little investigation risks serious or easily treatable causes of fatigue being overlooked, whilst too many increases the risk of iatrogenic harm and reduces the opportunity for early focused treatment.

A paper by Jones et al published this month in BMC Medicine may help clinicians in deciding how to undertake such investigations. Their results suggest that if clinicians look for common psychiatric and medical conditions in those complaining of prolonged fatigue, the rate of detection will be higher than previously estimated. The most common co-morbid condition identified was depression, suggesting a simple mental state examination remains the most productive single investigation in any new person presenting with unexplained fatigue. Currently, most diagnostic criteria advice CFS should not be diagnosed when an active medical or psychiatric condition which may explain the fatigue is identified.

We discuss a number of recent prospective studies that have provided valuable insights into the aetiology of chronic fatigue and describe a model for understanding chronic fatigue which may be equally relevant regardless of whether or not an apparent medical cause for fatigue can be identified. See the associated research paper by Jones et al: http://www.biomedcentral.com/1741-7015/7/57.

Comment on: An evaluation of exclusionary medical/psychiatric conditions in the definition of chronic fatigue syndrome. [BMC Med. 2009]

Source: Harvey SB, Wessely S. Chronic fatigue syndrome: identifying zebras amongst the horses. BMC Med. 2009 Oct 12;7:58. doi: 10.1186/1741-7015-7-58. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2766380/ (Full article)