Fatigue in primary Sjögren's syndrome is associated with an objective decline in physical performance, pain and depression
Bibliographic record
Abstract
OBJECTIVES: Fatigue is a major complaint in primary Sjögren's syndrome (pSS). To acquire a better understanding of fatigue in pSS, we investigated objective measures of performance decline (performance fatigability). Furthermore, we evaluated the relationship of self-reported fatigue with performance fatigability and factors modulating perceptions of fatigability (perceived fatigability). METHODS: Thirty-nine pSS patients and 27 healthy controls were included. To assess performance fatigability, force decline was measured during a sustained (124s) maximal voluntary contraction (MVC) with the index finger abductor muscle, and voluntary muscle activation was indexed using peripheral nerve stimulation. Self-reported fatigue was quantified using the Fatigue Severity Scale (FSS) and Modified Fatigue Impact Scale (MFIS). Pain, depression, and anxiety assessed using questionnaires and inflammatory biomarkers measured in blood were used as factors relating to perceived fatigability. RESULTS: Voluntary muscle activation was reduced in pSS (p=0.030), but force decline during the sustained MVC did not differ between groups. Self-reported fatigue was significantly higher in pSS than in controls (FSS: 4.4 vs. 2.6, p<0.001). Multivariable linear regression showed that both performance fatigability (force decline) and perceived fatigability (pain and depression) were associated with the MFIS physical domain in pSS (total explained variance of 47%). Negative associations with fatigue were observed for two interferon-associated proteins: MxA and CXCL10. CONCLUSIONS: This study demonstrates that performance fatigability in pSS was compromised by a reduced capacity of the central nervous system to drive the muscle. Furthermore, self-reported fatigue is a multifactorial symptom associated with both performance fatigability and perceived fatigability in patients with pSS.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".