Association of B12 deficiency and clinical neuropathy with metformin use in type 2 diabetes patients
Bibliographic record
Abstract
CONTEXT: Long-term metformin use has been hypothesized to cause B12 deficiency and neuropathy in Type 2 diabetes patients. However, there is a paucity of Indian data regarding the same. AIM: To compare the prevalence of B12 deficiency and peripheral neuropathy in patients with Type 2 diabetes mellitus treated with or without metformin. MATERIALS AND METHODS: We recruited patients with Type 2 diabetes and divided them into metformin exposed and nonmetformin exposed groups. We measured baseline demographic variables like age, sex, vegetarian status, and HbA1c levels in both groups. We compared vitamin B12 levels and severity of peripheral neuropathy (using Toronto Clinical Scoring System (TCSS)) in both groups. Definite B12 deficiency was defined as B12 <150 pg/ml and possible B12 deficiency as <220 pg/ml. The difference in vitamin B12 levels and TCSS was calculated in both groups using independent samples t-test. Spearman's rank correlation between cumulative metformin use and B12 level was calculated. Odds ratio of vitamin B12 deficiency in metformin exposed group was also estimated. RESULTS: Mean serum B12 levels was significantly lower in metformin exposed group (n=84) compared with nonmetformin exposed group (n=52) (410±230.7 versus 549.2±244.7, P=0.0011). Mean neuropathy score was significantly higher in metformin exposed group. (5.72±2.04 versus 4.62±2.12, P=0.0064). Odds ratio for possible B12 deficiency was 4.45 (95% CI 1.24-15.97). There was significant negative correlation between cumulative metformin dose and vitamin B12 level (r=-0.68, P<0.0001). CONCLUSION: Metformin use is associated with vitamin B12 deficiency and clinical neuropathy in Type 2 diabetes patients.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".