The effect of micro-particle curcumin on chronic kidney disease progression: the MPAC-CKD randomized clinical trial
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Bibliographic record
Abstract
BACKGROUND: Curcumin is a commonly used herbal supplement with anti-inflammatory and anti-fibrotic properties. Animal studies and small human trials suggest that curcumin reduces albuminuria in patients with chronic kidney disease (CKD). Micro-particle curcumin is a new, more bioavailable formulation of curcumin. METHODS: To determine whether micro-particle curcumin versus placebo slows the progression of albuminuric CKD we conducted a randomized, double-blind, placebo-controlled trial with 6-month follow-up. We included adults with albuminuria [a random urine albumin-to-creatinine ratio >30 mg/mmol (265 mg/g) or a 24-h urine collection with more than 300 mg of protein] and an estimated glomerular filtration rate (eGFR) between 15 and 60 mL/min/1.73 m2 within the 3 months before randomization. We randomly allocated participants 1:1 to receive micro-particle curcumin capsules (90 mg/day) or matching placebo for 6 months. After randomization, the co-primary outcomes were the changes in albuminuria and the eGFR. RESULTS: We enrolled 533 participants, but 4/265 participants in the curcumin group and 15/268 in the placebo group withdrew consent or became ineligible. The 6-month change in albuminuria did not differ significantly between the curcumin and placebo groups [geometric mean ratio 0.94, 97.5% confidence interval (CI) 0.82 to 1.08, P = .32]. Similarly, the 6-month change in eGFR did not differ between groups (mean between-group difference -0.22 mL/min/1.73 m2, 97.5% CI -1.38 to 0.95, P = .68). CONCLUSIONS: Ninety milligrams of micro-particle curcumin daily did not slow the progression of albuminuric CKD over 6 months. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02369549.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it