Long-term vitamin D and high-dose n-3 fatty acids’ supplementation improve markers of cardiometabolic risk in type 2 diabetic patients with CHD
Post-publication record
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Bibliographic record
Abstract
This study was performed to evaluate the effects of vitamin D and n-3 fatty acids' co-supplementation on markers of cardiometabolic risk in diabetic patients with CHD. This randomised, double-blinded, placebo-controlled trial was conducted among sixty-one vitamin D-deficient diabetic patients with CHD. At baseline, the range of serum 25-hydroxyvitamin D levels in study participants was 6·3-19·9 ng/ml. Subjects were randomly assigned into two groups either taking 50 000 IU vitamin D supplements every 2 weeks plus 2× 1000 mg/d n-3 fatty acids from flaxseed oil (n 30) or placebo (n 31) for 6 months. Vitamin D and n-3 fatty acids' co-supplementation significantly reduced mean (P = 0·01) and maximum levels of left carotid intima-media thickness (CIMT) (P = 0·004), and mean (P = 0·02) and maximum levels of right CIMT (P = 0·003) compared with the placebo. In addition, co-supplementation led to a significant reduction in fasting plasma glucose (β -0·40 mmol/l; 95 % CI -0·77, -0·03; P = 0·03), insulin (β -1·66 μIU/ml; 95 % CI -2·43, -0·89; P < 0·001), insulin resistance (β -0·49; 95 % CI -0·72, -0·25; P < 0·001) and LDL-cholesterol (β -0·21 mmol/l; 95 % CI -0·41, -0·01; P = 0·04), and a significant increase in insulin sensitivity (β +0·008; 95 % CI 0·004, 0·01; P = 0·001) and HDL-cholesterol (β +0·09 mmol/l; 95 % CI 0·01, 0·17; P = 0·02) compared with the placebo. Additionally, high-sensitivity C-reactive protein (β -1·56 mg/l; 95 % CI -2·65, -0·48; P = 0·005) was reduced in the supplemented group compared with the placebo group. Overall, vitamin D and n-3 fatty acids' co-supplementation had beneficial effects on markers of cardiometabolic risk.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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 | 0.001 | 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".