Evaluation of Parenteral Vitamin C's Effectiveness in Critically Ill Patients: A Systematic Review and Critical Appraisal
Bibliographic record
Abstract
Vitamin C, a key nutrient with potent antioxidant and immunomodulatory properties, has been explored for its therapeutic potential in treating severe infections, particularly sepsis. This systematic review aims to evaluate the effectiveness of parenteral vitamin C in improving clinical outcomes in patients with severe infections. A comprehensive search of several databases, including PubMed, EMBASE, and the Cochrane Library, was conducted for studies published between January 2000 and June 2024. Included were randomized controlled trials, observational studies, and case reports that examined the use of parenteral vitamin C in adult patients with severe infections. Data extracted included study design, sample size, intervention specifics, and clinical outcomes. Quality was assessed using tools appropriate to each study design, such as the Cochrane Risk of Bias Tool and the Newcastle-Ottawa Scale. The review included nine studies with diverse methodologies. While individual studies reported benefits such as improved immune function and reduced oxidative stress, larger systematic reviews and meta-analyses did not demonstrate a significant reduction in mortality. The results indicate that while parenteral vitamin C may improve certain biochemical and physiological parameters, these improvements do not consistently translate into enhanced survival or substantial clinical benefits. Parenteral vitamin C shows potential in modulating immune response and reducing oxidative damage in severe infections. However, its impact on key clinical outcomes like mortality and long-term recovery remains uncertain. This review highlights the need for further high-quality, randomized controlled trials to clarify vitamin C's role in managing severe infections and define optimal therapeutic protocols.
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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 | 0.020 | 0.065 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.010 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".