Perceived Versus Performance Fatigability in Patients With Rheumatoid Arthritis
Bibliographic record
Abstract
Rheumatoid arthritis (RA) is a chronic, inflammatory disease that affects 1% of the general population. Fatigue is a common complaint of patients with RA, however their perceived fatigue may be more exacerbated than objective measures of fatigue may indicate. The assessment of fatigue is made complex due to inconsistent and vague terms used to define fatigue, and the task dependence of fatigability. Fatigue is defined as a state of exhaustion and decreased strength, while fatigability indicates an individual's susceptibility to fatigue. In order to offer some clarity to the manifestation of fatigue in clinical populations, in this review we outline that fatigue should be described with subsections that are related to the symptom, such as: perceived fatigability and performance fatigability. Where perceived fatigability indicates the subjective state of the individual and thus involves the individual's subjective measure of fatigue, performance fatigability would be measured through clinical and laboratory-based assessments that quantify the functional decline in performance. This review describes RA and the various neuromuscular changes associated with the disease that can lead to alterations in both perceived and performance fatigue. From there, we discuss fatigue and RA, how fatigue can be assessed, effects of exercise interventions on RA symptoms and fatigue, and recommendations for future studies investigating subjective and objective measures of fatigability.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".