High-Dose Thiamine Supplementation in Older Patients With Heart Failure: A Pilot Randomized Controlled Crossover Trial (THIAMINE-HF)
Bibliographic record
Abstract
Background: Thiamine supplementation may improve cardiac function in older adults with heart failure (HF). Our objectives were to determine the following: (i) the feasibility of conducting a large trial of thiamine supplementation in HF; and (ii) the effects of thiamine on clinical outcomes. Methods: We conducted a double-blinded randomized placebo-controlled 2-period crossover feasibility study from June 2018 to April 2021. Adults aged ≥ 60 years with symptomatic HF and reduced ejection fraction (≤ 45%) were included. Participants were randomized to thiamine mononitrate 500 mg, or placebo, for 90 days and were switched to the opposite treatment for 90 days after a 6-week washout period. The primary feasibility outcome was recruitment of 24 participants in 11 months. Results: We screened 330 patients over 21 months to recruit 24 patients. Participants' mean age was 73.4 years. The targets for refusal rate, retention rate, and adherence rate were met. Nonsignificant improvements occurred in left ventricular ejection fraction and N-terminal pro-brain natriuretic peptide (NT-proBNP) level with thiamine. A total of 13 serious adverse events occurred in 7 patients; none were related to the study drug. Conclusions: Although we did not reach our recruitment target, we found high-dose thiamine supplementation to be well tolerated, with potential improvements in biomarker outcomes. A larger trial of thiamine supplementation is warranted.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".