Effect of Perioperative Vitamin C Supplementation on Postoperative Pain and the Incidence of Chronic Regional Pain Syndrome
Bibliographic record
Abstract
OBJECTIVES: Postoperative pain can contribute to increased risk for complications and lengthened hospital stays. The objective was to analyze the effects of perioperative vitamin C supplementation on postoperative pain and the development of complex regional pain syndrome I (CRPS I) in patients undergoing surgical procedures. MATERIALS AND METHODS: A systematic review of published literature was performed through April 2014. References from relevant studies were scanned for additional studies. Results were screened for relevance independently, and full-text studies were assessed for eligibility. Reporting quality was assessed using a modified Newcastle-Ottawa Scale. RESULTS: The search strategy yielded 710 studies, of which 13 were included: 7 on postoperative pain and 6 on CRPS I. In the final analysis, 1 relevant study found a reduction in postoperative morphine utilization after preoperative vitamin C consumption, whereas another showed no difference in postoperative pain outcomes between the vitamin C and control groups. A meta-analysis of 3 applicable CRPS I studies showed a decrease in postoperative CRPS I after perioperative vitamin C supplementation (relative risk=2.25; τ²=0). DISCUSSION: There is moderate-level evidence supporting the use of a 2 g preoperative dose of vitamin C as an adjunct for reducing postoperative morphine consumption, and high-level evidence supporting perioperative vitamin C supplementation of 1 g/d for 50 days for CRPS I prevention after extremity surgery. Additional studies are necessary to increase the level of evidence to determine the overall effectiveness and optimum dosage of vitamin C.
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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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".