The assessment of fatigue in primary Sjögren's syndrome
Bibliographic record
Abstract
OBJECTIVE: Disabling fatigue is a prominent feature of primary Sjögren's syndrome (PSS). We evaluated a number of questionnaires for their ability to discriminate fatigue in PSS from that in other rheumatic disorders and healthy controls. METHODS: 33 female caucasian patients with PSS, 45 with rheumatoid arthritis (RA), 16 with systemic lupus erythematosus (SLE) and 30 controls completed self-administered questionnaires including; Visual Analogue Scales (VAS), the Chalder Fatigue Scale (CFS), the Nottingham Health Profile (NHP) and the Medical Outcomes Short Form 36 Questionnaire (SF-36). RESULTS: All patient groups scored significantly worse than controls on the 'Energy' dimension of the NHP, the fatigue VAS and the 'Vitality' domain of the SF-36. No significant differences were observed between PSS patients and controls using the CFS. CONCLUSIONS: The NHP. VAS and SF-36 are useful in identifying fatigue in these rheumatic disorders. Further work is required to identify the characteristic features of fatigue in these conditions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".