Effect of metformin on blood lipids in patients with diabetes mellitus
Bibliographic record
Abstract
Background and objectives: Metformin improves macrovascular complications in people with diabetes mellitus (DM). Although the exact mechanism is not known, metformin has beneficial effects on dyslipidaemia. The aim of the study was to find out if there was an effect of metformin on blood lipids in people with diabetes mellitus. Method: This was a cross-sectional study which included 80 patients with diabetes mellitus. They were divided into 2 groups – (a) Group 1: on metformin and (b) Group 2: without metformin medication. None of the patients were on any other anti-diabetic medication. All data were obtained from patients’ medical records. Individual blood lipids and lipid ratios were compared between two groups. Result: Group 1 included 42 patients with a mean HbA1c of 7.58 ± 0.24% taking an average dose of 820.83 ± 60.40 mg/day of metformin. Group 2 consisted of 38 patients with mean HbA1c of 7.58 ± 0.29%. There was no significant difference in individual plasma lipid levels, lipoprotein ratio or frequency of dyslipidaemia between patients taking and not taking metformin (p>0.05). Also, different doses of metformin had no significant effect on the plasma lipid levels. Conclusion: Metformin did not affect the lipid profile of patients with diabetes mellitus. Ibrahim Med. Coll. J. 2019; 13(2): 23-27
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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 | 0.000 | 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 | 0.001 |
| 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".