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Record W2953091738 · doi:10.3389/fnut.2019.00080

Relation of Vegetarian Dietary Patterns With Major Cardiovascular Outcomes: A Systematic Review and Meta-Analysis of Prospective Cohort Studies

2019· review· en· W2953091738 on OpenAlexafffundabout
Andrea J. Glenn, Effie Viguiliouk, Maxine Seider, Beatrice A. Boucher, Tauseef Khan, Sonia Blanco Mejía, David J.A. Jenkins, Hana Kahleová, Dario Rahelić, Jordi Salas‐Salvadó, Cyril W.C. Kendall, John L. Sievenpiper

Bibliographic record

VenueFrontiers in Nutrition · 2019
Typereview
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsUniversity of TorontoUniversity of SaskatchewanSt. Michael's Hospital
FundersAgriculture and Agri-Food CanadaMerck Sharp and DohmeEuropean Association for the Study of DiabetesNovo NordiskHerbalife NutritionLoblaw Companies LimitedCoca-Cola FoundationCanola Council of CanadaHospital for Sick ChildrenDanish Cancer Society Research CenterAlpro FoundationPeanut InstituteCanadian Nutrition SocietyAmgenSoy Nutrition InstituteSaskatchewan Pulse GrowersInternational Nut and Dried Fruit CouncilAlmond Board of CaliforniaDiabetes CanadaDanoneArizona State UniversityCalifornia Strawberry CommissionU.S. Department of AgricultureAbbott LaboratoriesEli Lilly and CompanyKellogg'sProcter and GamblePfizerSanofiCanadian Institutes of Health ResearchPepsiCoAstraZeneca
KeywordsMedicineProspective cohort studyMeta-analysisCohort studyCohortInternal medicineDiabetes mellitusType 2 diabetesEndocrinology

Abstract

fetched live from OpenAlex

Background: Vegetarian dietary patterns are recommended for cardiovascular disease (CVD) prevention and management due to their favourable effects on cardiometabolic risk factors, however, the role of vegetarian dietary patterns in CVD incidence and mortality remains unclear. Objective: To update the European Association for the Study of Diabetes (EASD) clinical practice guidelines for nutrition therapy, we undertook a systematic review and meta-analysis of the association of vegetarian dietary patterns with major cardiovascular outcomes in prospective cohort studies that included individuals with and without diabetes using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach. Methods: MEDLINE, EMBASE, and Cochrane databases were searched through September 6th, 2018. We included prospective cohort studies ≥1 year of follow-up including individuals with or without diabetes reporting the relation of vegetarian and non-vegetarian dietary patterns with at least one cardiovascular outcome. Two independent reviewers extracted data and assessed study quality (Newcastle-Ottawa Scale). The prespecified outcomes included CVD incidence and mortality (total CVD, coronary heart disease (CHD) and stroke). Risk ratios for associations were pooled using inverse variance random effects model and expressed as risk ratios (RRs) with 95% confidence intervals (CIs). Heterogeneity was assessed (Cochran Q-statistic) and quantified (I2-statistic). The overall certainty of the evidence was assessed using GRADE. Results: Seven prospective cohort studies (197,737 participants, 8,430 events) were included. A vegetarian dietary pattern was associated with reduced CHD mortality (RR, 0.78 [CI, 0.69, 0.88]) and incidence (0.72 [0.61, 0.85]) but were not associated with CVD mortality (0.92 [0.84, 1.02]) and stroke mortality (0.92 [0.77, 1.10]). The overall certainty of the evidence was graded as “very low” for all outcomes, owing to downgrades for indirectness and imprecision. Conclusions: Very low-quality evidence indicates that vegetarian dietary patterns are associated with reductions in CHD mortality and incidence but not with CVD and stroke mortality in individuals with and without diabetes. More research, particularly in different populations, is needed to improve the certainty in our estimates. Registration: Clinicaltrials.gov, NCT03610828

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)0.019
metaresearch head score (Gemma)0.044
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 score0.019
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.044
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0160.033
Bibliometrics0.0080.009
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
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 head0.033
GPT teacher head0.282
Teacher spread0.249 · 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

Citations73
Published2019
Admission routes3
Has abstractyes

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