Important food sources of fructose-containing sugars and incident gout: a systematic review and meta-analysis of prospective cohort studies
Bibliographic record
Abstract
OBJECTIVE: Sugar-sweetened beverages (SSBs) are associated with hyperuricaemia and gout. Whether other important food sources of fructose-containing sugars share this association is unclear. DESIGN: To assess the relation of important food sources of fructose-containing sugars with incident gout and hyperuricaemia, we conducted a systematic review and meta-analysis of prospective cohort studies. METHODS: We searched MEDLINE, Embase and the Cochrane Library (through 13 September 2017). We included prospective cohort studies that investigated the relationship between food sources of sugar and incident gout or hyperuricaemia. Two independent reviewers extracted relevant data and assessed the risk of bias. We pooled natural-log transformed risk ratios (RRs) using the generic inverse variance method with random effects model and expressed as RR with 95% confidence intervals (CIs). The overall certainty of the evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation system. RESULTS: We identified three studies (1 54 289 participants, 1761 cases of gout), comparing the highest with the lowest level of exposure for SSBs, fruit juices and fruits. No reports were found reporting incident hyperuricaemia. Fruit juice and SSB intake showed an adverse association (fruit juice: RR=1.77, 95% CI 1.20 to 2.61; SSB: RR=2.08, 95% CI 1.40 to 3.08), when comparing the highest to lowest intake of the most adjusted models. There was no significant association between fruit intake and gout (RR 0.85, 95% CI 0.63 to 1.14). The strongest evidence was for the adverse association with SSB intake (moderate certainty), and the weakest evidence was for the adverse association with fruit juice intake (very low certainty) and lack of association with fruit intake (very low certainty). CONCLUSION: There is an adverse association of SSB and fruit juice intake with incident gout, which does not appear to extend to fruit intake. Further research is needed to improve our estimates. TRIAL REGISTRATION NUMBER: NCT02702375; Results.
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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 | 0.018 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.041 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".