Review of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: an evidence-based approach to diagnosis and management by clinicians
Bibliographic record
Abstract
This review was written from the viewpoint of the treating clinician to educate health care professionals and the public about Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS). It includes: the clinical definition of ME/CFS with emphasis on how to diagnose ME/CFS; the etiology, pathophysiology, management approach, long-term prognosis and economic cost of ME/CFS. After reading this review, you will be better able to diagnose and treat your patients with ME/CFS using the tools and information provided. Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, chronic medical condition characterized by symptom clusters that include: pathological fatigue and malaise that is worse after exertion, cognitive dysfunction, immune dysfunction, unrefreshing sleep, pain, autonomic dysfunction, neuroendocrine and immune symptoms. ME/CFS is common, often severely disabling and costly. The Institute of Medicine (IOM) reviewed the ME/CFS literature and estimates that between 836,000 and 2.5 million Americans have ME/CFS at a cost of between 17 and 24 billion dollars annually in the US. The IOM suggested a new name for ME/CFS and called it Systemic Exertion Intolerance Disease (SEID). SEID's diagnostic criteria are less specific and do not exclude psychiatric disorders in the criteria. The 2010 Canadian Community Health Survey discovered that 29% of patients with ME/CFS had unmet health care needs and 20% had food insecurity--lack of access to sufficient healthy foods. ME/CFS can be severely disabling and cause patients to be bedridden. Yet most patients (80%) struggle to get a diagnosis because doctors have not been taught how to diagnose or treat ME/CFS in medical schools or in their post-graduate educational training. Consequently, the patients with ME/CFS suffer. They are not diagnosed with ME/CFS and are not treated accordingly. Instead of compassionate care from their doctors, they are often ridiculed by the very people from whom they seek help. The precise etiology of ME/CFS remains unknown, but recent advances and research discoveries are beginning to shed light on the enigma of this disease including the following contributors: infectious, genetic, immune, cognitive including sleep, metabolic and biochemical abnormalities. Management of patients with ME/CFS is supportive symptomatic treatment with a patient centered care approach that begins with the symptoms that are most troublesome for the patient. Pacing of activities with strategic rest periods is, in our opinion, the most important coping strategy patients can learn to better manage their illness and stop their post-exertional fatigue and malaise. Pacing allows patients to regain the ability to plan activities and begin to make slow incremental improvements in functionality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".