A randomized trial of icosapent ethyl in ambulatory patients with COVID-19
Bibliographic record
Abstract
The coronavirus disease 2019 (COVID-19) pandemic remains a source of considerable morbidity and mortality throughout the world. Therapeutic options to reduce symptoms, inflammatory response, or disease progression are limited. This randomized open-label trial enrolled 100 ambulatory patients with symptomatic COVID-19 in Toronto, Canada. Results indicate that icosapent ethyl (8 g daily for 3 days followed by 4 g daily for 11 days) significantly reduced high-sensitivity C-reactive protein (hs-CRP) and improved symptomatology compared with patients assigned to usual care. Specifically, the primary biomarker endpoint, change in hs-CRP, was significantly reduced by 25% among treated patients (-0.5 mg/L, interquartile range [IQR] [-6.9,0.4], within-group p = 0.011). Conversely, a non-significant 5.6% reduction was observed among usual care patients (-0.1 mg/L, IQR [-3.2,1.7], within-group p = 0.51). An unadjusted between-group primary biomarker analysis was non-significant (p = 0.082). Overall, this report provides evidence of an early anti-inflammatory effect of icosapent ethyl in a modest sample, including an initial well-tolerated loading dose, in symptomatic outpatients with COVID-19. ClinicalTrials.gov Identifier: NCT04412018.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".