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Record W2944273773 · doi:10.1136/bmjopen-2018-024171

Important food sources of fructose-containing sugars and incident gout: a systematic review and meta-analysis of prospective cohort studies

2019· review· en· W2944273773 on OpenAlexafffund
Sabrina Ayoub‐Charette, Qi Liu, Tauseef Khan, Fei Au‐Yeung, Sonia Blanco Mejía, Russell J. de Souza, Thomas M.S. Wolever, Lawrence A. Leiter, Cyril W.C. Kendall, John L. Sievenpiper

Bibliographic record

VenueBMJ Open · 2019
Typereview
Languageen
FieldMedicine
TopicDiet, Metabolism, and Disease
Canadian institutionsImpactMcMaster UniversityUniversity of TorontoSt. Michael's Hospital
FundersInstitute of Nutrition, Metabolism and DiabetesCanadian Institutes of Health ResearchCanadian Nutrition Society
KeywordsMedicineMeta-analysisGoutFructoseEnvironmental healthProspective cohort studyCohort studySugarSystematic reviewFood scienceMEDLINEInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.550
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0230.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.240
GPT teacher head0.476
Teacher spread0.236 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations68
Published2019
Admission routes2
Has abstractyes

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