Platelet Reactivity and Disease Activity in Subjects with Psoriatic Arthritis
Bibliographic record
Abstract
OBJECTIVE: Platelet aggregation plays a major role in vascular mortality. Individuals with psoriatic arthritis (PsA) are highly predisposed to vascular mortality. We evaluated the correlation between disease activity and platelet aggregation in individuals with PsA. METHODS: Individuals with PsA receiving tumor necrosis factor-α (TNF-α) blockers (n = 114) and healthy controls (n = 114) matched for age, sex, and cardiovascular risk factors were tested for light transmission aggregometry. None was receiving antiinflammatory drugs. Platelet aggregation (max-A%) was defined as maximal light transmittance achieved within 5 min after the addition of 0.1 or 0.2 mM arachidonic acid or 0.4 μM adenosine diphosphate. A value of ≥ 50% irreversible light transmittance (LT-50%) following platelet stimulation was used to define platelet hyperreactivity. Minimal disease activity (MDA) was evaluated in subjects with PsA. RESULTS: Regardless of the agent used, individuals with PsA showed a higher max-A% and achieved LT-50% more often than controls. Among individuals with PsA, those achieving MDA exhibited a max-A% similar to that of controls, both being significantly lower (p < 0.001) than max-A% of subjects with active disease. Subjects with active disease showed platelet hyperreactivity (LT-50%) more often than those achieving MDA (p < 0.001). For increasing quartiles of max-A%, C-reactive protein levels increased and prevalence of MDA decreased. CONCLUSION: Compared with those achieving MDA, subjects with active PsA disease had abnormally high platelet reactivity. Whether this is relevant for the cardiovascular risk profile of subjects with PsA receiving TNF-α blockers requires further evaluation.
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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 | 0.001 |
| 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 | 0.000 | 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".