Micronutrient status of patients with diabetic foot: A systematic review.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Micronutrient status encompasses a range of indicators that reflect the levels and balance of macro- and microelements, as well as vitamins within the body. These essential substances, required in minimal amounts, are crucial for supporting normal physiological processes, immune system functioning, and tissue repair. The aim of this systematic review is to summarize data on the deficiency or excess of microelements, macroelements, and vitamins in patients with diabetic foot ulcers. METHODS AND STUDY DESIGN: Databases were searched for studies on vitamin, macronutrient, micronutrient levels and their impact on the course, treatment and healing of diabetic foot ulcers. The Cochrane Risk of Bias tool was employed for assessing randomized trials, while the Newcastle-Ottawa Scale was utilized for evaluating observa-tional studies in terms of quality and bias risk. RESULTS: The findings revealed a notable correlation between deficiencies in vitamins D, C, A and the severity of clinical symptoms. Low vitamin D levels were linked to elevated proinflammatory cytokines. Higher concentrations of folate and vitamin B-12 were associated with improved ulcer healing, supplementation with zinc and magnesium contributed to a reduction in ulcer size. Inadequate intake of zinc, vitamins E, C was found to compromise antioxidant defences. Elevated ferritin levels may serve as an indicator of inflammation. CONCLUSIONS: The most important task is to adjust the in-take of micronutrients to maintain balance and prevent deficiency and excess, which is important in the complex therapy of patients.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.006 | 0.007 |
| 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".