A randomized double-blind cross-over trial to study the effects of resistant starch prebiotic in chronic kidney disease (ReSPECKD)
Bibliographic record
Abstract
BACKGROUND: Chronic kidney disease (CKD) is associated with a reduced quality of life and an increased risk of kidney failure, cardiovascular events, and all-cause mortality. Accumulation of nitrogen-based uremic toxins leads to worsening of symptoms in individuals with CKD. Many uremic toxins, such as indoxyl and p-cresol sulphate, are produced exclusively by the gut microbiome through the proteolytic digestion of aromatic amino acids. Strategies to reduce the production of these toxins by the gut microbiome in individuals with CKD may lessen symptom burden and delay the onset of dialysis. One such strategy is to change the overall metabolism of the gut microbiome so that less uremic toxins are produced. This can be accomplished by manipulating the energy source available to the microbiome. Fermentable carbohydrates which reach the gut microbiome, like resistant starch (RS), have been shown to inhibit or reduce bacterial amino acid metabolism. This study aims to investigate the effects of resistant potato starch (RPS) as a prebiotic in individuals with CKD before the onset of dialysis. METHODS: This is a double-blind, randomized two-period crossover trial. Thirty-six eligible participants will consent to follow a 26-week study regimen. Participants will receive 2 sachets per day containing either 15 g of RPS (MSPrebiotic, resistant potato starch treatment) or 15 g cornstarch (Amioca TF, digestible starch control). Changes in blood uremic toxins will be investigated as the primary outcome. Secondary outcomes include the effect of RPS consumption on symptoms, quality of life and abundance, and diversity and functionality of the gut microbiome. DISCUSSION: This randomized trial will provide further insight into whether the consumption of RPS as a prebiotic will reduce uremic toxins and symptoms in individuals who have CKD. TRIAL REGISTRATION: ClinicalTrials.gov NCT04961164 . Registered on 14 July 2021.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".