The Need for ib r ddition in ymp omatic eart ailure (FEAST-HF): A Randomized Controlled Pilot Trial
Bibliographic record
Abstract
Background: ailure (FEAST-HF) trial evaluated feasibility of recruitment and supplementation with FDF in HF and whether FDF (acacia), compared to control, reduced the level of N-terminal pro-b-type natriuretic peptide (NT-proBNP) and growth stimulation expressed gene 2 (ST2), and produced changes in the gut microbiome. Methods: Participants were randomly allocated 1:1:1 to either of the intervention arms (5 g/d or 10 g/d acacia) or to the control arm (10 g/d microcrystalline cellulose (MCC; nonfermentable active control). Adherence and tolerance were assessed, and clinical events were monitored for safety. All outcomes (NT-proBNP, ST2, New York Heart Association class, Kansas City Cardiomyopathy Questionnaire scores, 6-minute walk test score, gut microbiome) were measured at baseline, and at 6 and 12 weeks. Results: Between September 13, 2018 and December 16, 2021, 51 patients were randomly allocated to either MCC (n = 18), acacia 5 g daily (n = 13), or acacia 10 g daily (n = 18). No differences occurred between either dose of acacia and MCC in NT-proBNP level, ST2, New York Heart Association class, or questionnaire scores over 12 weeks. Dietary treatment arms had a negligible impact on microbial communities. No safety, tolerability, or adherence issues were observed. Conclusions: Dietary supplementation with acacia gum was both safe and well tolerated in ambulatory patients with HF; however, it did not change NT-proBNP level, ST2, or the composition of the gut microbiome.ClinicalTrials.gov: NCT03409926.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".