Impact of low <i>v.</i> moderate intakes of long-chain <i>n</i>-3 fatty acids on risk of coronary heart disease
Bibliographic record
Abstract
The objective of the present study was to determine whether the consumption of ≥ 250 v. < 250 mg of the long-chain n-3 fatty acids (n-3 LCFA) per d is associated with a reduction in the risk of fatal and non-fatal CHD in individuals with no prior history of CHD. A comprehensive and systematic review of the published scientific literature resulted in the identification of eight prospective studies (seven cohorts and one nested case-control study) that met predefined inclusion criteria. Relative to the consumption of < 250 mg n-3 LCFA per d, the consumption of ≥ 250 mg/d was associated with a significant 35·1 % reduction in the risk of sudden cardiac death and a near-significant 16·6 % reduction in the risk of total fatal coronary events, while the risk of non-fatal myocardial infarction was not significantly reduced. In several meta-analyses, which were based on US studies, risk of CHD death was found to be dose-dependently reduced by the n-3 LCFA, with further risk reductions observed with intakes in excess of 250 mg/d. Prospective observational and intervention data from Japan, where intake of fish is very high, suggest that n-3 LCFA intakes of 900 to 1000 mg/d and greater may confer protection against non-fatal myocardial infarction. Thus, the intake of 250 mg n-3 LCFA per d may, indeed, be a minimum target to be achieved by the general population for the promotion of cardiovascular health.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".