Plasma Total Homocysteine and its Relationship with Cardiovascular Disease
Bibliographic record
Abstract
Aims: The specific aim of this review was to compile the first systematic review of systematic reviews and meta-analyses from a range of studies that evaluates the evidence that elevated homocysteine may be a risk factor for CVD. Data Synthesis: 379 entries were identified by initial screening using set criteria revealing eleven meta-analyses, one systematic review, two systematic reviews/meta-analyses and ten other studies, between 1994 and 2013.These studies compared homocysteine levels and its relationship with twelve different types of CVD chronic conditions. Final methodological quality assessment was conducted independently using the instrument AMSTAR for the systematic reviews and meta-analyses. The remaining studies were assessed using data extraction tools from JBI QARI, Appendix 2 & 4 packages. Conclusions: From the selected studies, 82.8% of the CVD conditions demonstrated that epidemiologic and clinical data strongly indicated that elevated homocysteine levels is a risk factor for primary CVD. 71.4% of the CVD conditions demonstrated that plasma tHcy can be employed as an independent biomarker. Despite 46.2% of the CVD conditions finding that reducing plasma tHcy lowers the risk of many CVD events, it remains unclear whether the reduction in plasma tHcy will reduce the risk of some CVD events; it is therefore considered prudent to take precautionary measures to aim for normal levels of homocysteine to avoid the risk of developing or exacerbating CVD. Moreover, it was shown that levels of homocysteine can be profoundly affected by diet, supplementation and lifestyle. The present study will help to clarify the present scientific understanding of this subject.
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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 | 0.015 | 0.051 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.014 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| 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".