Signal Hyperintensities on Brain Magnetic Resonance Imaging in Patients with Primary Sjögren Syndrome and Frequent Episodic Tension-type Headache: Relation to Platelet Serotonin Level and Disease Activity
Bibliographic record
Abstract
OBJECTIVE: To examine differences in number and size of signal hyperintensities (SH) on magnetic resonance imaging (MRI) between patients with primary Sjögren syndrome (pSS) and controls who all had frequent episodic tension-type headache (FETH), and to investigate their relation to platelet serotonin level (PSL), patient age, disease duration, and activity. METHODS: SH in 22 pSS patients with FETH were compared to 20 aged-matched controls with FETH, using the modified semiquantitative rating scale. Spectrofluorimetry was used for determination of PSL, and the European League Against Rheumatism SS Disease Activity Index (ESSDAI) for disease activity assessment. RESULTS: Statistically significant differences in the total number of SH were noted infratentorially (p = 0.025) and in the basal ganglia for lesions of diameter > 5 mm (p = 0.048). Significant correlations were found between disease duration and number of overall lesions > 5 mm (p = 0.04) and subcortical lesions of diameter 2-5 mm (p = 0.035). Number of periventricular SH inversely correlated to PSL (p = 0.019) and to patient age (p = 0.004), without association with markers of immunoinflammation and ESSDAI. CONCLUSION: Our study showed that SH on brain MRI are more common in specific regions of the brain in pSS patients with FETH than in controls with FETH, signifying a more widespread cerebral vasculopathy in SS patients with FETH. Periventricular SH seem to be associated to increased platelet serotonin release in pSS patients with FETH and correlated with disease duration, without correlation to the actual ESSDAI and markers of immunoinflammation, and might be linked with chronic immunoinflammation of low-grade intensity and vasculitis in 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".