The Effect of Dietary Pulses on Lipids in Controlled Feeding Trials: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Background Although there is evidence from controlled feeding trials that dietary pulses (beans, peas, chickpeas, and lentils) may benefit lipid control, cardiovascular guidelines have not addressed dietary pulses in their recommendations. Aim A systematic review and meta‐analysis was conducted to assess the effect of dietary pulses on established therapeutic lipid targets for cardiovascular risk reduction. Methods We searched MEDLINE, EMBASE, Cochrane, and CINAHL databases through June 13 2011 and included human trials of at least 3 weeks in duration. Data were pooled by the generic inverse variance method using random effects models and expressed as mean differences (MD) with 95% confidence intervals. Heterogeneity was assessed (Chi2) and quantified (I2). Study quality was assessed using the Heyland Methodological Quality Score (MQS). Results 24 isocaloric trials (n= 808) met the inclusion criteria. Diets supplemented with dietary pulses significantly lowered LDL‐C levels (MD= −0.22 [95% CI: −0.32, −0.12]) and non‐HDL‐C (MD= −0.24 [95% CI: −0.37, −0.11]) compared with isocaloric control diets. No significant effects were observed for TC:HDL, ApoB, and ApoB:ApoA. Limitation The majority of trials were of low quality. Conclusions Pooled analyses demonstrated that dietary pulses significantly improved LDL‐C and non‐HDL levels. Funding: Pulse Canada, Saskatchewan Pulse Growers Grant Funding Source : ASN
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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 | 0.028 | 0.066 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.033 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".