Lessening Organ dysfunction with VITamin C (LOVIT): protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Sepsis is a health problem of global importance; treatments focus on controlling infection and supporting failing organs. Recent clinical research suggests that intravenous vitamin C may decrease mortality in sepsis. We have designed a randomized controlled trial (RCT) to ascertain the effect of vitamin C on the composite endpoint of death or persistent organ dysfunction at 28 days in patients with sepsis. METHODS: LOVIT (Lessening Organ dysfunction with VITamin C) is a multicenter, parallel-group, blinded (participants, clinicians, study personnel, Steering Committee members, data analysts), superiority RCT (minimum n = 800). Eligible patients have sepsis as the diagnosis for admission to the intensive care unit (ICU) and are receiving vasopressors. Those admitted to the ICU for more than 24 h are excluded. Eligible patients are randomized to high-dose intravenous vitamin C (50 mg/kg every 6 h for 96 h) or placebo. The primary outcome is a composite of death or persistent organ dysfunction (need for vasopressors, invasive mechanical ventilation, or new and persisting renal replacement therapy) at day 28. Secondary outcomes include persistent organ dysfunction-free days to day 28, mortality and health-related quality of life at 6 months, biomarkers of dysoxia, inflammation, infection, endothelial function, and adverse effects (hemolysis, acute kidney injury, and hypoglycemia). Six subgroup analyses are planned. DISCUSSION: This RCT will provide evidence of the effect of high-dose intravenous vitamin C on patient-important outcomes in patients with sepsis. TRIAL REGISTRATION: clinicaltrials.gov, NCT03680274, first posted 21 September 2018.
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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 | 0.051 | 0.052 |
| Meta-epidemiology (narrow) | 0.009 | 0.003 |
| Meta-epidemiology (broad) | 0.017 | 0.009 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.012 |
| Insufficient payload (model declined to judge) | 0.093 | 0.015 |
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".