Design and population of the VALOR-CKD study: a multicenter, randomized, double-blind, placebo-controlled trial evaluating the efficacy and safety of veverimer in slowing progression of chronic kidney disease in patients with metabolic acidosis
Bibliographic record
Abstract
BACKGROUND: Whether treating metabolic acidosis slows progression of chronic kidney disease (CKD) has not been established. Veverimer is a novel hydrochloric acid binder that removes acid from the gastrointestinal tract leading to an increase in serum bicarbonate; it is being developed to treat metabolic acidosis with the goal of slowing progression of CKD. METHODS: The VALOR-CKD trial is an international, randomized, multicenter, double-blind, placebo-controlled study designed to evaluate the effect of once-daily veverimer on kidney disease progression in patients with metabolic acidosis and CKD. Eligibility criteria include a serum bicarbonate in the range of 12-20 mmol/L and an estimated glomerular filtration rate (eGFR) of 20-40 mL/min/1.73 m2. The primary outcome is kidney disease progression defined as the development of end-stage kidney disease, a sustained decline in eGFR of >40% from baseline or death due to kidney failure. Key secondary endpoints include effects on physical function. RESULTS: Between December 2018 and December 2021, 1480 participants were randomized. The mean age at baseline was 65.1 years and 42% of the patients were female. The mean baseline eGFR was 29.1 mL/min/1.73 m2 and mean serum bicarbonate was 17.5 mmol/L. The median urine albumin-to-creatinine ratio at screening was 201 mg/g and the median 5-year predicted risk of kidney failure was 32%. Diabetes and hypertension were present in 56% and 98% of participants, respectively. CONCLUSIONS: VALOR-CKD has recruited a large population of people with metabolic acidosis at high risk for CKD progression to determine the effects of veverimer on the risk of progressive loss of kidney function.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".