The effects of low-dose colchicine on the progression of aortic valve stenosis: Rationale, design, and baseline characteristics of the Colchicine and Inflammation in Aortic Stenosis (CHIANTI) trial
Bibliographic record
Abstract
ABSTRACT BACKGROUND Aortic valve stenosis (AS) is one of the most common valvular heart diseases worldwide. Its prevalence increases with age and is expected to rise further as the population ages. Untreated severe AS carries a two-year mortality rate exceeding 50%. Furthermore, surveillance and management of AS impose a significant burden on healthcare systems. Therefore, effective pharmacological strategies are urgently needed to slow or halt the progression of AS. RATIONALE AND DESIGN Inflammation plays a central role in the pathogenesis of both atherosclerosis and AS. Anti-inflammatory therapy with low-dose colchicine reduces cardiovascular events in patients with coronary artery disease, but its efficacy has not been tested in AS. Colchicine and Inflammation in Aortic Stenosis (CHIANTI) is an investigator-initiated, placebo-controlled, double-blind, multicenter, randomized trial involving 150 patients with moderate AS. After confirming tolerance during a two-week run-in phase, eligible participants underwent coronary computed tomography (CT) angiography, 18 F-sodium fluoride ( 18 F-NaF) positron emission tomography (PET)-CT, and echocardiography. Thereafter, participants were randomized 1:1 to colchicine 0.5 mg once daily or a matching placebo. All baseline imaging is repeated after 24 months. The primary endpoint is the change in aortic valve calcium score on CT. Secondary endpoints are (I) the change in aortic valve 18 F-NaF uptake on PET-CT and corrected for target-to-background ratio, and (II) the change in peak aortic jet velocity on echocardiography. CONCLUSION The CHIANTI trial evaluates whether anti-inflammatory therapy with low-dose colchicine can slow or halt the progression of moderate AS. If successful, it would offer the first effective pharmacological treatment for AS. TRIAL REGISTRATION Registered on ClinicalTrials.gov ( https://clinicaltrials.gov/ ), ID: NCT05162742.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".