Protective Effect of Metformin on Venous Thrombosis in Diabetic Patients: Findings From a Systematic Review
Bibliographic record
Abstract
Background: Despite the effects of metformin on cardiovascular diseases, there is limited evidence supporting its beneficial effects on venous thrombosis, and such evidence is not qualitatively synthesized both from observational and intervention studies, thereby limiting our understanding of the role of metformin in preventing venous thromboembolism (VTE). Thus, we carried out a systematic review of the epidemiological studies assessing the role of metformin in preventing VTE among diabetic patients. Methods: A systematic search of three main electronic databases including Embase, PubMed, and EBSCO was undertaken in 2021. Any study conducted between 2000 and 2021 that addressed the role of metformin in preventing venous thrombosis in patients diagnosed with type 2 diabetes mellitus was considered eligible. Results: Following a comprehensive review of the research articles based on the eligibility criteria, six articles were incorporated into the review. The findings of the review demonstrate that metformin was found to be associated with 22% to 58% risk reduction for venous thrombosis among diabetic patients. However, due to the observational studies included in the meta-analysis, the protective effect may not be independent of other risk factors or other variables. Conclusion: Overall, the findings showed a beneficial effect of metformin against venous thrombosis, meaning that metformin may play a vital role in preventing deep venous thrombosis among patients diagnosed diabetes mellitus. However, future studies are warranted before making any conclusions about the efficacy of metformin against venous thrombosis in diabetic patients. J Endocrinol Metab. 2022;12(6):161-167 doi: https://doi.org/10.14740/jem848
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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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.009 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| 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".