A comparison between the effects of flaxseed oil and fish oil supplementation on cardiovascular health in type 2 diabetic patients with coronary heart disease: A randomized, double‐blinded, placebo‐controlled trial
Bibliographic record
Abstract
This study compared the effects of flaxseed and fish oil supplementation on cardiovascular risk parameters in diabetic patients with coronary heart disease. Participants were randomly allocated into three intervention groups to receive either 1,000 mg of omega-3 fatty acids from fish oil or 1,000 mg of omega-3 fatty acids from flaxseed oil or placebo (n = 30 each group) twice a day for 12 weeks. A significant reduction in insulin levels (.04) was observed following flaxseed oil and fish oil supplementation compared with the placebo. In addition, a significant reduction in high-sensitivity C-reactive protein (.02) was seen after flaxseed oil supplementation compared with the placebo and a significant increase in total nitrite (.001) was seen after flaxseed oil and fish oil intake compared with placebo. Additionally, a significant increase in total antioxidant capacity (p < .001) after consuming flaxseed oil and fish oil compared with placebo and glutathione levels (.001) after consuming fish oil compared with flaxseed oil and placebo was observed. Overall, our study revealed the beneficial effects of flaxseed oil and fish oil supplementation on few metabolic profiles. This study suggests that the effect of flaxseed oil in reducing insulin and increasing total nitrite and total antioxidant capacity is similar to fish oil.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".