Chronic fatigue syndrome (CFS)/Myalgic Encephalomyelitis (ME) and Fibromyalgia (FM): the foundation of a relationship
Bibliographic record
Abstract
INTRODUCTION: Chronic fatigue syndrome (CFS)/Myalgic Encephalomyelitis (ME) and fibromyalgia (FM) are both debilitating syndromes with complex polysymptomatology. Early research infers that a relationship may exist even though the diagnosis provided may influence the management trajectory. In the absence of a diagnostic test and treatment, this study aims to confirm the symptoms and their severity, which may infer a relationship and influence future research. METHOD: A quasi-experimental design was utilised, using Internet-based self-assessment questionnaires focusing on nine symptom areas: criteria, pain, sleep, fatigue, anxiety and depression, health-related quality of life, self-esteem and locus of control. The questionnaires used for data collection are as follows: the American Centre for Disease Control and Prevention Symptom Inventory for CFS/ME (American CDC Symptom Inventory); the American College of Rheumatology (ACR) Criteria for FM; Fibromyalgia Impact Questionnaire (FIQ); McGill Pain Questionnaire (MPQ); Multidimensional Fatigue Inventory (MFI); Pittsburgh Sleep Quality Index (PSQI); Health-Related Quality of Life SF-36 V2 (HRQoL SF-36 V2); Hospital Anxiety and Depression Scale (HADS); Multidimensional Health Locus of Control (MHLOC) and the Rosenberg Self-Esteem Scale (RSES). SETTING AND PARTICIPANTS: Participants were recruited from two distinct community groups, namely CFS/ME (n = 101) and FM (n = 107). Participants were male and female aged 17 (CFS/ME mean age 45.5 years; FM mean age 47.2 years). RESULTS: All participants in the CFS/ME and FM groups satisfied the requirements of their individual criteria. Results confirmed that both groups experienced the debilitating symptoms measured, with the exception of anxiety and depression, impacting on their quality of life. Results suggest a relationship between CFS/ME and FM, indicating the requirement for future research.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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".