Vitamin C Administration to the Critically Ill: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Vitamin C, an enzyme cofactor and antioxidant, could hasten the resolution of inflammation, oxidative stress, and microvascular dysfunction. While observational studies have demonstrated that critical illness is associated with low levels of vitamin C, randomized controlled trials (RCTs) of vitamin C, alone or in combination with other antioxidants, have yielded contradicting results. We searched MEDLINE, EMBASE, CINAHL, and the Cochrane Central Register of Controlled Trials (inception to December 2017) for RCTs comparing vitamin C, by enteral or parenteral routes, with placebo or none, in intensive care unit (ICU) patients. Two independent reviewers assessed study eligibility without language restrictions and abstracted data. Overall mortality was the primary outcome; secondary outcomes were incident infections, ICU length of stay (LOS), hospital LOS, and duration of mechanical ventilation (MV). We prespecified 5 subgroups hypothesized to benefit more from vitamin C. Eleven randomized trials were included. When 9 RCTs (n = 1322) reporting mortality were pooled, vitamin C was not associated with reduced risk of mortality (risk ratio [RR] 0.72, 95% confidence interval [CI]: 0.43-1.20, P = .21). No effect was found on infections, ICU or hospital LOS, or duration of MV. In multiple subgroup comparison, no statistically significant subgroup effects were observed. However, we did observe a tendency towards a mortality reduction (RR 0.21; 95% CI: 0.04-1.05; P = .06) when intravenous high-dose vitamin C monotherapy was administered. Current evidence does not support supplementing critically ill patients with vitamin C. A moderately large treatment effect may exist, but further studies, particularly of monotherapy administration, are warranted.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".