Tree nuts improve criteria of the metabolic syndrome: a systematic review and meta‐analysis of randomized controlled dietary trials (1025.6)
Bibliographic record
Abstract
Background: Chronic disease guidelines support tree nut consumption alone or as part of dietary patterns to reduce cardiovascular risk, based on their favorable LDL‐C lowering effect. The effects of nuts on metabolic risk factors other than LDL‐C, however, remain uncertain. Aim: To assess the effect of tree nuts on criteria of the metabolic syndrome, we conducted a systematic review and meta‐analysis of randomized controlled dietary trials. Methods: We searched MEDLINE, EMBASE, CINAHL, and the Cochrane Library (through March 19, 2013). We included relevant randomized controlled trials (RCTs) of 蠅 3 weeks reporting at least 1 criterion of metabolic syndrome. Two independent reviewers extracted all relevant data. Data were pooled using the generic inverse variance method using random effects models and expressed as mean differences (MD) with 95% confidence intervals (CI). Heterogeneity was assessed by Chi² and quantified by I². Study quality was assessed. Results: Eligibility criteria were met by 39 RCTs including 1,676 participants who were otherwise healthy or had dyslipidemia, metabolic syndrome or diabetes mellitus. Tree nut interventions lowered triglycerides compared with control diet interventions (MD=‐0.07 mmol/L [95%CI, ‐0.11, ‐0.04 mmol/L]), but had no effects on waist circumference, HDL‐C, blood pressure, or fasting blood glucose with the direction of effect favoring tree nuts for all except HDL‐C. Limitations: Most of the trials were of short duration (<12 weeks) and of poor quality (MQS<8). Substantial unexplained heterogeneity remained in most analyses. Conclusions: Pooled analyses show a net benefit of tree nuts for metabolic syndrome with decreases in triglycerides across nut types and no adverse effects on other criteria. Longer and higher quality trials are needed. Protocol registration: Clinicaltrials.gov identifier NCT01630980 Grant Funding Source : Supported by the International Tree Nut Council Nutrition Research & Education Foundation
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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 | 0.024 | 0.060 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.040 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".