The Effect of Vitamin C and E on Lipid Profile in Type 2 Diabetes Mellitus Patients
Bibliographic record
Abstract
Introduction: Diabetes mellitus is one of the most common metabolic disorders that cause micro- and macro-vascular complications. Because of cardiovascular disease is common in T2DM, lipid abnormalities should be evaluated in diabetes. As vitamin C, E are known for their helpful effects on plasma lipids and glycated hemoglobin (HbA1c), we evaluated the effect of these vitamins on blood glucose, plasma lipids in individuals with type 2 diabetes mellitus.Methods: The study was carried out in 170 T2DM on consumption of vitamin C, E, combination of C & E and placebo. The subjects comprised of two main groups, supplementation and placebo group which supplementation group consists of 3 sub-groups. Each sub- group received three capsules per day for a period of three months. HbA1c, glucose and lipid profile were determined in baseline and after three months with receiving supplement.Results: A significant decrease in FBS, TG, LDL, cholesterol and HbA1c was seen in the supplemented groups. Conclusion: This study demonstrated that patients with T2DM after three months consumption of vitamins C, E and C&E showed significantly lowered hypertension and improved insulin action and decrease lipid profile.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".