Diet Quality Indices in Relation to Cardiovascular Risk Factors in T2DM Patients: A Systematic Review
Bibliographic record
Abstract
Background: Dietary quality indices are practical as an instrument to investigate the extent of adhering to a special diet to prevent cardiovascular disease (CVD) in type 2 diabetes mellitus (T2DM). Considering the lack of any systematic review with regards to this issue, our aim was to examine observational studies to test the relationship between dietary quality indices and CVD risk factors in T2DM. Methods: Systematic search was performed in Web of knowledge, PubMed, Cochrane, Science direct, Google Scholar and Scopus databases from January 1990 to July 2020. The studies exploring the relationship between dietary quality indices (diet quality score (DQS), dietary diversity score (DDS), healthy diet indicator (HDI), healthy eating index (HEI), diet quality index (DQI), Mediterranean diet score (MDS)) and lipid profile, anthropometric indices, glucose profile as well as blood pressure were eligible to be included in this review. Overall, mean changes, odd ratio (RR), correlation coefficients, and beta coefficient of outcomes were extracted, with the quality assessment of studies performed applying The Newcastle-Ottawa scale. Results: From among 1627 papers, 10 articles were included: Eight cross-sectional and two prospective (cohort) studies. The association between HEI as well as MDS and CVD risk factors was more evident in the included studies. Fasting blood sugar, hemoglobin A1c, body mass index, and waist circumference revealed the greatest inverse significant relationship with dietary quality indices in adults with T2DM. Conclusion: Overall, the findings of this study suggest that the level of CVD risk factors in T2DM decreases significantly with increase in the score of dietary quality indices. Further studies in future are required to confirm these findings.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.009 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".