Evaluating case diagnostic criteria for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS): toward an empirical case definition
Bibliographic record
Abstract
PURPOSE: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is an illness characterized by a variety of symptoms including post-exertional malaise, unrefreshing sleep, and cognitive impairment. A variety of case definitions (e.g., the Canadian Consensus Criteria (CCC), the Myalgic Encephalomyelitis International Consensus Criteria (ME-ICC), and the Institute of Medicine (IOM) criteria) have been used to diagnose patients. However, these case definitions are consensus-based rather than empirical. MATERIALS AND METHODS: = 2308) of ME/CFS symptom data. We performed primary and secondary exploratory factor analyses on the DePaul Symptom Questionnaire's 54-item symptom inventory. These results were compared to the CCC, the ME-ICC, and the IOM criteria. RESULTS: We identified seven symptom domains, including post-exertional malaise, cognitive dysfunction, and sleep dysfunction. Contrary to many existing case criteria, our analyses did not identify pain as an independent factor. CONCLUSIONS: Although our results implicate a factor solution that best supports the CCC, revisions to the criteria are recommended.Implications for rehabilitationME/CFS is a chronic illness with no consensus regarding case diagnostic criteria, which creates difficulty for patients seeking assistance and disability benefits.The current study compared three commonly used case definitions for ME/CFS by factor analyzing symptomological data from an international sample of patients.Our results suggest three primary and four secondary symptom domains which differed from all three case definitions.These findings could help reduce barriers to care for those disabled with ME/CFS by guiding the development of an empirically-based case definition.
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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 | 0.032 | 0.155 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".