The impact of vitamin D supplementation on peripheral neuropathy in a sample of Egyptian prediabetic individuals
Bibliographic record
Abstract
Background: Vitamin D deficiency is seen more frequently in diabetic patients with distal symmetrical polyneuropathy . Unfortunately, there is a shortage of data concerning prediabetic individuals with peripheral neuropathy (PN). Therefore, we aimed to study the association of vitamin D deficiency with PN severity and to determine the effect of vitamin D supplementation on PN in prediabetics. Methods : A case-control study was conducted consisting of 178 prediabetic individuals recruited from the outpatient department of the National Institute of Diabetes and Endocrinology, Cairo, Egypt. All patients were screened for PN using clinical examination and Douleur Neuropathique 4 diagnostic questionnaire (DN4). They were divided into 89 patients with and 89 patients without PN (group A and B). Group A was assessed for neuropathic severity using the Short-Form McGill Pain Questionnaire (SF-MPQ). In addition, 25-hydroxyvitamin D, ionized calcium, phosphorus, parathyroid hormone (PTH), glycated hemoglobin (HbA1c), fasting blood glucose (FBG), 2-hour post 75g glucose (2h-75g glucose) and lipid profile were measured. Prediabetic patients with PN were given vitamin D3 200.000 IU IM monthly for three months. After three months, clinical assessment, DN4, SF-MPQ and all laboratory measures were repeated. Results: Vitamin D level was negatively correlated with neuropathy score and severity (r = -0.65, -0.47, p <0.001) among group A. Moreover, vitamin D level was an independent predictor of neuropathic severity (odds ratio -0.18, 95% CI -0.33 -0.03, P ≤ 0.05). Supplementation of vitamin D resulted in a highly significant improvement in glycemic parameters and lipid profile, p ≤ 0.001. Interestingly, neuropathy score and severity before vitamin D supplementation were (6.4 ± 1.6 and 28.3 ± 7.2) and after became (2.5 ± 0.9 and 17 ± 6.3, p ≤ 0.001). Conclusion: Vitamin D deficiency is an independent risk factor for PN. Correction of vitamin D deficiency improves glycemic parameters, PN score and severity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".