Defining the prevalence and symptom burden of those with self-reported severe chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME): a two-phase community pilot study in the North East of England
Bibliographic record
Abstract
OBJECTIVES: To define the prevalence of severe chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) and its clinical characteristics in a geographically defined area of Northern England. To understand the feasibility of a community-based research study in the severely affected CFS/ME group. DESIGN: A two-phase clinical cohort study to pilot a series of investigations in participants own homes. SETTING: Participants were community living from the area defined by the Northern clinical network of the UK. PARTICIPANTS: Adults with either a medical or a self-reported diagnosis of CFS/ME. Phase 1 involved the creation of a database. Phase 2: five participants were selected from database, dependent on their proximity to Newcastle. INTERVENTIONS: The De Paul fatigue questionnaire itemised symptoms of CFS/ME, the Barthel Functional Outcome Measure and demographic questions were collected via postal return. For phase 2, five participants were subsequently invited to participate in the pilot study. RESULTS: 483 questionnaire packs were requested, 63 were returned in various stages of completion. 56 De Paul fatigue questionnaires were returned: all but 12 met one of the CFS/ME criteria, but 12 or 22% of individuals did not fulfil the Fukuda nor the Clinical Canadian Criteria CFS/ME diagnostic criteria but 6 of them indicated that their fatigue was related to other causes and they barely had any symptoms. The five pilot participants completed 60% of the planned visits. CONCLUSIONS: Severely affected CFS/ME individuals are keen to participate in research, however, their symptom burden is great and quality of life is poor. These factors must be considered when planning research and methods of engaging with such a cohort.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".