Effect of tree nuts on glycemic control in diabetes: a systematic review and meta‐analysis of randomized controlled dietary trials (1025.16)
Why this work is in the frame
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Bibliographic record
Abstract
Background: Tree nut consumption is associated with reduced diabetes risk, however, results from randomized trials on glycemic control have been inconsistent. Aim: We conducted a systematic review and meta‐analysis of randomized controlled trials to assess the effect of tree nuts on glycemic control in individuals with diabetes. Methods: We searched MEDLINE, EMBASE, CINAHL, and Cochrane databases through 14 May 2013 for relevant randomized trials 蠅3‐weeks reporting HbA1c, fasting glucose, fasting insulin, and/or HOMA‐IR. Two independent reviewers extracted relevant data. Data were pooled using the generic inverse variance method and expressed as mean differences (MD) with 95% confidence intervals (CI). Heterogeneity was assessed by Cochran’s Q and quantified by I2. Results: 10 trials (n=374) met the eligibility criteria. Diets emphasizing tree nuts significantly lowered HbA1c (MD=‐0.11 %, 95% CI:‐0.18, ‐0.04 %; P=0.001) and fasting glucose (MD=‐0.20 mmol/L, 95% CI:‐0.38, ‐0.03 mmol/L; P=0.02) compared with isocaloric control diets. No significant treatment effects were observed for fasting insulin and HOMA‐IR. Limitations: Majority of trials were of poor quality and short duration. Conclusion: Pooled analyses show diets high in tree nuts improve glycemic control in individuals with type 2 diabetes. Longer, higher quality trials are needed. Clinicaltrials.gov identifier: NCT01630980 Grant Funding Source : International Tree Nut Council Nutrition Research & Education Foundation
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.055 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.071 | 0.016 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it