IV Vitamin C in Adults With Sepsis: A Bayesian Reanalysis of a Randomized Controlled Trial*
Bibliographic record
Abstract
OBJECTIVES: The Lessening Organ Dysfunction with Vitamin C trial showed a harmful effect of vitamin C on 28-day death or persistent organ dysfunction. To maximize interpretation, we present a post hoc Bayesian reanalysis. DESIGN: Bayesian reanalysis of a randomized placebo-controlled trial. SETTING: Thirty-five ICUs. PATIENTS: Adults with proven or suspected infection, vasopressor support, and no more than 24 hours of ICU admission. INTERVENTIONS: Patients were allocated to receive either vitamin C (50 mg/kg of body weight) or placebo every 6 hours for up to 96 hours. MEASUREMENTS AND MAIN RESULTS: The primary outcome was the composite of death or persistent organ dysfunction (i.e., vasopressor use, invasive mechanical ventilation, or new renal replacement therapy) at 28 days. We used Bayesian log-binomial models with random effects for hospital site and varying informative prior beliefs for the effect of vitamin C to estimate risk ratios (RRs) with 95% credible intervals (Crls) in the intention to treat population (vitamin C, 435 patients; placebo, 437 patients). Using weakly neutral priors, patients allocated to vitamin C had a higher risk of death or persistent organ dysfunction at 28 days (RR, 1.20; 95% Crl, 1.04-1.39; probability of harm, 99%). This effect was consistent when using optimistic (RR, 1.14; 95% Crl, 1.00-1.31; probability of harm, 98%) and empiric (RR, 1.09; 95% Crl, 0.97-1.22; probability of harm, 92%) priors. Patients allocated to vitamin C also had a higher risk of death at 28 days under weakly neutral (RR, 1.17; 95% Crl, 0.98-1.40; probability of harm, 96%), optimistic (RR, 1.10; 95% Crl, 0.94-1.30; probability of harm, 88%), and empiric (RR, 1.05; 95% Crl, 0.92-1.19; probability of harm, 76%) priors. CONCLUSIONS: The use of vitamin C in adult patients with proven or suspected infection and vasopressor support is associated with high probability of harm.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.146 | 0.226 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.021 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".