The Fifth Element: Is Vascular Dysfunction an Intrinsic Feature of Gout?
Bibliographic record
Abstract
Gout, the most common inflammatory arthritis, affects as many as 5.1% of the adult population. Classically, gout is conceived as four sequential phenotypic states: 1) asymptomatic hyperuricemia 2) acute gout flare 3) inter-critical gout (gout between flares); and 4) tophaceous gout. However, these four states are paralleled by a fifth state, consisting of vascular involvement. The mechanisms and consequences of vascular gout are incompletely elucidated. In vitro and animal models indicate that soluble urate adversely affects vascular endothelium and smooth muscle. The recent discovery that soluble urate can be transported intracellularly to alter cell metabolism and epigenetics (trained innate immunity) suggests additional impacts of urate on leukocytes and endothelium. Once gout has progressed to flares, the vasculature is exposed to inflammatory mediators, both during flares and to a lesser but persistent extent inter-critically, suggesting additional mechanisms of gout's effect. We have reported that patients with gout have diminished endothelial function measured by brachial artery flow-mediated dilation. ACR gout guideline-concordant treatment improves endothelial function but is less effective in patients with cardiometabolic comorbidities. Moreover, treatment of gout patients with the anti-inflammatory colchicine and urate lowering therapy improves endothelial function and reduces the risk of both incident coronary artery disease (CAD), and MACE in patients with established CAD.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".