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Record W2171894730 · doi:10.4103/jpgm_20146001_96

Comment on: Association of B12 deficiency and clinical neuropathy with metformin use in type 2 diabetes patients

2014· article· en· W2171894730 on OpenAlexaboutno aff
Mukta N. Chowta, Gaurav Tiwary

Bibliographic record

VenueJournal of Postgraduate Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsnot available
Fundersnot available
KeywordsMetforminMedicineDiabetes mellitusMalabsorptionInternal medicineType 2 diabetesConfoundingPeripheral neuropathyDiseaseVitamin D and neurologyVitamin B12vitamin D deficiencyEndocrinology

Abstract

fetched live from OpenAlex

Sir, With reference to the aricle on ‘Association of B12 deficiency and clinical neuropathy with metformin use in type 2 diabetes patients, we would like to put forth our views.[1] The article by itself has no new message. Several studies have examined this association and the mechanisms involved. In addition, the design used by the authors may not be sufficient to prove a cause-effect relationship. Exhaustion of vitamin B12 stores usually occurs after 12 - 15 years of absolute vitamin B12 deficiency. Hence, the duration of therapy with metformin is an important parameter to be considered. In addition, the authors have not compared the duration of diabetes among those taking metformin versus those not taking metformin, although they mention that data regarding the duration of diabetes had been collected. The duration of disease is thus a major confounding factor, as it increases the chances of peripheral neuropathy, which by itself is a complication of the disease. Hence, two groups must be comparable with regard to duration of disease too. Many diabetic patients are also likely to receive vitamin supplementation, which has not been addressed. Absorption of the vitamin B12 -intrinsic factor complex is calcium-dependent and metformin interferes with this absorption. In support of this hypothesis, there is evidence that dietary calcium supplementation reverses metformin-induced vitaminB12 malabsorption.[2] Hence, patients taking calcium supplementation also need to have been excluded. Similarly, there are many other medications that can cause vitamin B12 deficiency. Also, the use of the Toronto Clinical Scoring system (TCSS) does not address bias adequately (Investigator blinded only to the laboratory results, but not to the group allocation). Another finding is that the number of patients having neuropathy was much more than the number of patients having vitamin B12 deficiency (44 vs. 25 in the metformin-treated group). This discrepancy definitely points to other causes of peripheral neuropathy in these patients, as expected (diabetic neuropathy). [Figure 1] in the article has shown the correlation of cumulative doses of metformin with vitamin B12 deficiency with out mention of the unit.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.046
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.034
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.046
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0040.001
Research integrity0.0340.030
Insufficient payload (model declined to judge)0.0070.006

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.

Opus teacher head0.031
GPT teacher head0.300
Teacher spread0.269 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations8
Published2014
Admission routes1
Has abstractyes

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