SNF472 Consistently Slows Progression of Coronary Artery Calcification Across Subgroups of Patients on Hemodialysis
Bibliographic record
Abstract
Background: In the CaLIPSO study, SNF472 significantly attenuated progression of coronary artery calcium (CAC) volume score compared with placebo. This pre-specified analysis examined CAC progression in key subgroups. Methods: Patients were randomized to SNF472 300 mg (n=92), SNF472 600 mg (n=91) or placebo (n=91) infused 3x/week during hemodialysis (HD) for 52 weeks on top of standard care therapy determined by each investigator. We examined change in log CAC volume score from baseline to week 52 in the combined SNF472 dose groups vs placebo for subgroups of age, sex, diabetes, dialysis vintage, arteriosclerotic cardiovascular disease (ASCVD), use of non-Ca phosphate binders, Ca-based phosphate binders, calcimimetics, activated vitamin D, warfarin, or statins in the modified ITT population (mITT, defined as subjects who received at least one dose of study drug and had an evaluable post-baseline CT scan). Results: Baseline characteristics were similar across treatment groups: mean age was 64 y, 39% were female; 62% had diabetes, and 41% had prior ASCVD. Median HD vintage was 42 mo; 33% received HD for ≥5 years. Concomitant medications at baseline were: 62% non-Ca phosphate binders, 28% Ca-based phosphate binders, 31% calcimimetics, 51% activated vit D, 8% warfarin, and 64% statins. In the overall mITT, CAC volume progression was 11% in the combined SNF472 groups vs 20% in placebo (p=0.016). Treatment differences for CAC volume progression were similar across subgroups (Figure). All interaction p-values were non-significant and comparisons favored SNF472 vs placebo in each subgroup. Conclusions: SNF472 treatment for 52 weeks attenuated CAC progression compared with placebo in all subgroups. Funding: Commercial Support - Sanifit
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".