Metformin reduces circulating malondialdehyde-modified low-density lipoprotein in type 2 diabetes mellitus
Bibliographic record
Abstract
PURPOSE: Type 2 diabetes is known to be associated with increasing cardiovascular mortality. Malondialdehyde-modified LDL (MDA-LDL) is an oxidized LDL and is increased in patients with diabetes or hypertriglyceridemia. Elevated MDA-LDL has been reported to be a risk factor of atherosclerosis or cardiovascular disease. Sitagliptin is a dipeptidyl peptidase-4 inhibitor and a new class of hypoglycemic agents. In this study, the effects of increasing the dose of metformin and add-on sitagliptin on MDA-LDL were examined in type 2 diabetes patients. METHODS: Seventy patients with type 2 diabetes, inadequately controlled despite on-going treatment with metformin 500 mg/day, were enrolled in this randomized controlled trial. The patients received additional metformin (500 mg/day) or sitagliptin (50 mg/day) for 6 months, and changes in metabolic parameters including MDA-LDL were evaluated. RESULTS: After 6 months of treatment, add-on sitagliptin (n=35) improved fasting blood glucose (FBG) and hemoglobin A1c (HbA1c) to significantly greater extent than increasing the dose of metformin (n=35). There were no differences in total cholesterol and low-density lipoprotein cholesterol levels between two groups. MDA-LDL levels (mean ± S.E.) decreased significantly with increasing the dose of metformin (from 94.40 ± 6.35 to 77.83 ± 4.74 U/L, P < 0.005), but remained unchanged with add-on sitagliptin treatment (from 89.94 ± 5.59 to 98.46 ± 6.78 U/L, p > 0.05). Multiple linear regression analysis identified increasing the dose of metformin treatment as the only independent factor associated with decreased MDA-LDL (β coefficient 0.367, P < 0.0119), and no significant correlation between change in MDA-LDL and fasting blood glucose or HbA1c. CONCLUSION: These results suggest that increasing the dose of metformin improves serum MDA-LDL levels in type 2 diabetes mellitus.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".