Design of the fish oil inhibition of stenosis in hemodialysis grafts (FISH) study
Bibliographic record
Abstract
BACKGROUND: Arteriovenous grafts (AVG) are the predominant form of permanent vascular access used among hemodialysis (HD) patients in North America but suffer from high intervention and complication rates associated with vascular stenosis. The fish oil inhibition of stenosis in hemodialysis grafts (FISH) study evaluates the efficacy of fish oil in improving HD graft patency. METHODS: This study is a multi-center, randomized, double blind placebo-controlled clinical trial of 232 chronic HD patients who require a new graft access. Participants are randomized to fish oil versus placebo post-operatively. The primary endpoint is the proportion of AVG with loss of native patency within 12 months of creation. Secondary endpoints are aimed to determine the effect of fish oil on factors that may promote stenosis and thrombosis. Cumulative patency rates, survival analysis, and analysis of inflammatory markers and adverse events will provide a better understanding of the potential effect of fish oil on a patient's vascular access and cardiovascular system. The FISH study is registered at current controlled trials (www.controlled-trials.com) ISRCTN: 15838383. RESULTS: Details of the study protocol are described including mechanisms of reducing bias through randomization and double blinding, sample size determination, evaluation of patient adherence, access monitoring, and the safety of using fish oil. The main challenges of designing and implementing this study, including using a natural supplement as an intervention in modern medical practice and recruitment of graft recipients in the ;fistula first' environment are discussed. CONCLUSION: This is the first large, multicenter, randomized controlled trial of a natural supplement in preventing HD graft stenosis and thrombosis.
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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 | 0.016 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".