Effects of Vitamin C on Organ Function in Cardiac Surgery Patients: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Cardiac surgery is associated with oxidative stress and systemic inflammation, which both contribute to postoperative organ dysfunction. Vitamin C is a pleiotropic, antioxidant, and potentially organ-protective micronutrient. Past clinical trials and meta-analyses have focused predominantly on occurrence of postoperative atrial fibrillation. Therefore, we investigated the influence of perioperative vitamin C administration on clinically relevant parameters closer related to the patient’s recovery, especially organ function, and overall outcomes after cardiac surgery. Methods: Randomized controlled trials (RCTs) comparing perioperative vitamin C administration versus placebo or standard of care in adult patients undergoing cardiac surgery were identified through systematic searches in Pubmed, EMBASE, and CENTRAL on 23 November 2018. Published and unpublished data were included. Assessed outcomes include organ function after cardiac surgery, adverse events, in-hospital mortality, intensive care unit, and hospital length-of-stay. Data was pooled only when appropriate. Results: A total of 19 RCTs with 2008 patients were included in this meta-analysis. Vitamin C significantly decreased the incidence of atrial fibrillation (p = 0.008), ventilation time (p < 0.00001), ICU length-of-stay (p = 0.004), and hospital length-of-stay (p < 0.0001). However, on average, vitamin C had no significant effects on in-hospital mortality (p = 0.76), or on the incidence of stroke (p = 0.82). High statistical heterogeneity was observed in most analyses. Conclusions: Vitamin C impacts clinically and economically important outcomes, such as ICU and hospital length-of-stay, duration of mechanical ventilation and lowers the incidence of atrial fibrillation. Due to missing reports on organ dysfunction, this meta-analysis cannot answer the question, if vitamin C can improve single- or multiorgan function after cardiac surgery.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| 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".