The Power of Vitamin C: A Scoping Review of Pressure Injury Wound Healing with Vitamin C Supplementation
Bibliographic record
Abstract
BackgroundPressure injuries are a significant health concern in Canada, with the occurrence as high as 26% across all health care settings. Researchers have studied the effectiveness of vitamin C in the healing of pressure injuries. The purpose of this scoping review is to synthesize the existing literature on the role of vitamin C in pressure injury wound healing and identify gaps within the current literature landscape. MethodsA scoping review of the literature was conducted using the framework developed by Arksey and O’Malley, along with the PRISMA-ScR guidelines. PubMed, Medline, CINAHL, and EMBASE databases were searched for human studies published in English that investigated the effectiveness of vitamin C in reducing wound size and/or accelerating the rate of pressure injury healing. The authors extracted data using a predefined form to summarize information on study type, patient descriptions, study design, interventions, and outcomes. ResultsNine articles met the review criteria. Six were randomized control trials, and the remaining 3 were observational studies. Seven studies acknowledged the benefit of vitamin C in pressure injury wound healing. One study reported no observed difference in healing within the control and treatment groups, and 1 study did not support the idea of increased vitamin C for wound healing. ConclusionThe current evidence suggests a possible correlation between vitamin C supplementation and pressure injury wound healing. Research with randomized control trial study designs that have large sample sizes is necessary to investigate the exclusive role of vitamin C and its impact on pressure injury wound healing.
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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 | 0.044 | 0.164 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.024 | 0.023 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| 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".