Effects of Metformin Alone or in Combination With Insulin on Bone Mineral Density in Osteopenic Patients With Type 2 Diabetes
Bibliographic record
Abstract
Background: Patients with diabetes are at risk for osteoporotic fractures. We propose to test the hypothesis that treatment of diabetes mellitus with metformin alone or in combination with insulin affects bone mineral density (BMD) in a positive way possibly via the Wnt/beta-catenin pathway. Methods: We retrospectively reviewed records of veterans at the Memphis Veterans Administration Medical Center (VAMC) with type 2 diabetes on treatment with metformin alone or in combination with insulin found to have osteopenia by dual-energy X-ray absorptiometry (DXA) between 2002 and 2013. Change in BMD over time was compared with age, race and sex matched controls. Results: Of 1,662 patients with DXA scans, we had two study groups (13 patients on metformin and insulin; 20 on metformin alone). These patients were compared to age, race and sex matched controls not on metformin, insulin or thiazolidinediones ( TZDs). On follow-up (1 - 6 years) of both study groups, there was no statistical difference in average BMD over time compared to controls (P = 0.172 in combination group, P = 0.747 in metformin alone group). However, there was improvement in BMD over time at the right and left femoral neck in the metformin alone group compared to control (left femur P = 0.130; right femur P = 0.017). Conclusions: In this retrospective study, there was a trend towards improvement in BMD in osteopenic patients with type 2 diabetes treated with metformin. The exact mechanism by which metformin exerts positive effects on bone is yet to be fully elucidated . We propose that metformin may promote bone formation by decreasing sclerostin levels, an inhibitor of the Wnt/beta-catenin pathway. Overall, we surmise that the osteo-anabolic effect of metformin on BMD still needs to be further studied in a larger prospective study. J Endocrinol Metab. 2014;4(4):89-92 doi: http://dx.doi.org/10.14740/jem234w
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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 | 0.001 | 0.003 |
| 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".