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Relation of Fructose‐Containing Sugars with Cardiovascular Disease: A Systematic Review and Meta‐Analysis of Prospective Cohort Studies

2017· review· en· W4389020207 on OpenAlexafffundabout
Tauseef Khan, Sonia Blanco Mejía, Russell J. de Souza, Cyril W.C. Kendall, John L. Sievenpiper

Bibliographic record

VenueThe FASEB Journal · 2017
Typereview
Languageen
FieldMedicine
TopicDiet, Metabolism, and Disease
Canadian institutionsMcMaster UniversityUniversity of TorontoUniversity of SaskatchewanSt. Michael's Hospital
FundersCanadian Diabetes Association
KeywordsMedicineProspective cohort studyRelative riskMeta-analysisCohort studyCochrane LibraryFructoseInternal medicineCohortConfidence intervalFood scienceChemistry

Abstract

fetched live from OpenAlex

Objective Sugars‐sweetened beverages are associated with increased risk of cardiovascular disease (CVD). To assess whether this association holds for the fructose‐containing sugars they contain, we conducted a systematic review and meta‐analysis of prospective cohort studies. Methods MEDLINE, EMBASE and Cochrane Library (through October 31, 2016) were searched for relevant studies. We included prospective cohort studies investigating the association between fructose‐containing sugars (total sugars, fructose, sucrose and added sugars) and incident CVD. Two independent reviewers reviewed and extracted the relevant data and assessed study quality (Newcastle‐Ottawa Scale). Risk estimates of extreme comparisons (lowest versus highest quantile) were pooled using inverse variance random effects models and expressed as risk ratios (RR) with 95% confidence intervals (95% CI). Inter‐study heterogeneity was assessed with Cochran Q statistic and quantified with the I 2 statistic. The overall quality of the evidence was assessed using the Grading of recommendations assessment, development, and evaluation (GRADE). Results The eligibility criteria were met by 7 prospective cohort studies (10 cohort comparisons) involving 530,268 individuals and 15,657 incident cases of CVD observed over an average follow‐up of 11.2 years. Total sugars (RR, 1.07 [95% CI, 1.01 to 1.13]) and fructose (RR, 1.08 [95% CI, 1.01 to 1.15]) but not sucrose (RR, 0.97 [95% CI, 0.88 to 1.07]) or added sugars (RR, 1.03 [95% CI, 0.85 to 1.24]) were associated with increased incidence of CVD. There was no evidence of heterogeneity in any of the analyses except for added sugars which showed evidence of substantial heterogeneity (I 2 =82%, P=0.004). The overall quality of the evidence was graded as “very low quality” for all associations owing to a downgrade for serious imprecision for total sugars, fructose, and sucrose and separate downgrades for serious imprecision and serious inconsistency for added sugars. Conclusions Current evidence does not allow us to conclude with certainty that all fructose‐containing sugars are associated with increased risk of CVD owing to the very low quality of evidence and the inconsistency across types of sugars. Further research should confirm whether the adverse association seen between sugars‐sweetened beverages and CVD applies to other important food sources of sugars. Protocol registration: clinicaltrials.gov identifier, NCT01608620 Support or Funding Information Canadian Diabetes Association, Canadian Institutes of Health Research, Banting and Best Diabetes Centre and PSI Foundation

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.034
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.034
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0150.036
Bibliometrics0.0070.009
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.105
GPT teacher head0.370
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2017
Admission routes3
Has abstractyes

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