100% Fruit Juice Intake, Glucose Profile, and Uric Acid: A Systematic Review
Bibliographic record
Abstract
Several studies suggest a favorable effect of 100% fruit juice (100%FJ) on cardio-metabolic risk. However, international dietary guidelines disagree on recommendations regarding fruit drink consumption, and the published European Food Safety Authority draft, based only on epidemiological data, suggested a direct relationship between 100%FJ intake and the development of type 2 diabetes mellitus (T2DM) and gout. Thus, we performed a systematic review of both randomized controlled trials (RCT) and prospective studies that assessed the relationship between 100%FJ intake, uric acid metabolism, and glucose profile. Concerning previous meta-analyses, no new prospective studies were identified for the evaluation of T2DM, and no studies were identified for the assessment of gout risk in the general population; conversely, 3 studies were detected for the assessment of gestational diabetes risk. Moreover, new RCTs were detected and included in an updated meta-analysis on glucose profile and uric acid. 100%FJ intake was associated with a decrease in uric acid, and neutral associations were found for different markers of glucose metabolism and the risk of gestational diabetes. In summary, this meta-analysis confirmed that there was no difference between 100%FJ intake and the comparator on glucose metabolism. It also showed that 100%FJ intake resulted in lower levels of uric acid than the comparator. In addition, the analysis indicated a neutral effect of 100%FJ on gestational diabetes. Finally, the systematic review confirmed the neutral effect of 100%FJ on T2DM and suggested the need for further studies to evaluate the risk of gout.
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How this classification was reachedexpand
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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| 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 | 0.001 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".