The correlation between vitamin D deficiency and the severity of painful diabetic neuropathy in patients with type 2 diabetes mellitus (T2DM)
Bibliographic record
Abstract
Background: Diabetes and its complications are the major burden health problem worldwide, and diabetic neuropathy is one of the major complications. Vitamin D levels found to be significantly lower in people with painful diabetic peripheral neuropathy compared with healthy people. The data about the vitamin D levels and severity of the neuropathy in Indonesia are very limited.Objective: This study aims to investigate the possible relationship between vitamin D levels and the severity of diabetic peripheral neuropathy.Methods: A cross-sectional study was carried out during the period from October 2019 to December 2019 on 53 subjects with diabetic peripheral neuropathy. The patient’s clinical profile including age, gender, and duration of diabetes, HbA1c, and associated microvascular complications was documented. The treatment history was recorded from electronic prescribing data. The severity of neuropathy was measured with the Toronto Clinical Neuropathy Scoring System. Serum 25-OH vitamin D levels were measured by enzyme immunoassays for the quantitative measurement of total serum 25-OH Vitamin D level in ng/mL.Results: Vitamin D levels based on the severity of neuropathy are divided into mild, moderate, and severe. At mild neuropathy severity, the average patient's vitamin D level was 19±8.85ng/mL, at moderate severity the patient's vitamin D level was 16.25±6.08 ng/mL, and for severe neuropathy, the average vitamin D level was 13.35±6.20 ng/mL. Spearman correlation test obtained r value= -0.439 and p value=0.001.Conclusions: There is a moderate, significant, and negative patterned correlation between vitamin D level and diabetic peripheral neuropathy 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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".