Systematic review and meta-analysis of the correlation between plasma homocysteine levels and coronary heart disease
Bibliographic record
Abstract
Background: With the progresses in medical development in recent years, plasma homocysteine (Hcy) levels are considered to be an independent risk factor for the development of coronary heart disease (CHD). We hope to use the method of meta-analysis to systematically evaluate the relationship between plasma Hcy levels and CHD, for providing a basis for the prevention, diagnosis and treatment of CHD. Methods: The PubMed, Cochrane and Embase databases were searched for case-control studies and cohort studies on the association between plasma Hcy levels and CHD from the database establishment to October 2021. Duplicate studies were re-excluded by Endnote X9 software. The risk of bias was assessed using the Newcastle-Ottawa Scale (NOS) scale. All of the studies we included were studies with no confirmed CHD and recorded Hcy levels. The data were extracted, and the quality was evaluated. Data were recorded and meta-analyzed using Stata 15.1 software. The risk ratio (RR) values were combined with 95% confidence interval (CI) using fixed- or random-effects models. Finally, sensitivity analysis was used to assess the reliability of the results. A funnel plot was used to evaluate the publication bias of the literature. Results: A total of 10 studies with a total of 10,103 subjects were included. All studies were of case-control studies or cohort studies with good quality. Meta-analysis showed that for every 5 µmol/L increase in Hcy level, the pooled risk ratio of coronary events was 1.22, 95% CI: 1.11, 1.34. These results demonstrate that when plasma Hcy level increased, the risk of CHD also increased. Conclusions: Compared with traditional risk factors, the incidence of CHD increases by 22% for every 5 µmol/L increase in plasma Hcy levels. This mean that clinicians can timely take preventive measures for coronary heart disease when the patients' elevated plasma Hcy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".