D-Dimer Levels as a Marker of Cutaneous Disease Activity
Bibliographic record
Abstract
IMPORTANCE: Biochemical markers of disease allow clinicians to monitor disease severity, progression, and response to treatment. C-reactive protein and erythrocyte sedimentation rate are commonly used biochemical markers of inflammatory disease. We present 2 cases that indicate that D-dimer levels may be useful as a potential biochemical marker of disease activity in certain cutaneous inflammatory conditions. OBSERVATIONS: We report 2 cases in which clinical disease activity correlates with D-dimer levels. The first case is a woman in her 50s with a diagnosis of cutaneous polyarteritis nodosa. The second case is a man in his 20s with recurrent urticaria. In both patients, plasma D-dimer levels increased with clinical evidence of disease activity and decreased with treatment and resolution of the disease flare. Interestingly, serum C-reactive protein levels did not correlate with disease activity and were found to be normal during clinically active disease. CONCLUSIONS AND RELEVANCE: We show the potential value of D-dimer measurements as a marker of vasculocentric and/or vasculopathic inflammation and suggest that vascular endothelial damage may be ongoing in certain cutaneous inflammatory conditions.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".