Red meat consumption, risk of incidence of cardiovascular disease and cardiovascular mortality, and the dose–response effect
Bibliographic record
Abstract
BACKGROUND: Red and (particularly) processed meats are high in cholesterol and saturated and solid fatty acids. Their consumption is considered one of the risk factors for metabolic disorders. Numerous studies demonstrated a possible association between red meat consumption and cardiovascular disease (CVD). In this protocol, we propose a systematic review of the literature to examine the associations of red meat consumption with CVD incidence and mortality, and explore the potential dose-response relationship. METHODS: We will search MEDLINE/PubMed, Scopus, SciELO, LILACS, ScienceDirect, Web of Science, Cochrane (CENTRAL), WHOLIS, PAHO, and Embase. We will include prospective epidemiological studies (longitudinal cohort). Risk of bias will be assessed using the Newcastle-Ottawa scale (NOS). Four independent researchers will conduct all evaluations. Disagreements will be referred to a fifth reviewer. We will summarize our findings using a narrative approach and tables to describe the characteristics of the included studies. The heterogeneity between trial results will be evaluated using a standard chi-squared test with P < .05. We will conduct the study in accordance with the guideline of the Preferred Reporting Items for Systematic Review and Meta-analyses Protocols (PRISMA-P). RESULTS: This review will evaluate the association between red meat consumption and incidence of CVD and mortality (primary outcome measures). The secondary outcome measure will include the dose-response effect. CONCLUSION: The findings of this systematic review will summarize the latest evidence of the association between red meat consumption and incidence of CVD and mortality and the dose-response effect through a systematic review and meta-analysis. REGISTRATION: PROSPERO CRD42019100914.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".