A Meta-Analysis of Essential Trace Elements in Patients with Coronary Heart Disease
Bibliographic record
Abstract
There is growing evidence that presence of essential trace elements that pose risk for coronary heart disease (CHD) patients. A meta-analysis was conducted on the levels of trace elements Copper (Cu), Zinc (Zn), Iron (Fe), Manganese (Mn), Cobalt (Co) and Chromium (Cr) in CHD patients. Eligible articles from the databases of Web of Science, Scopus, PubMed, EBSCOHost and Ovid were searched based on PRISMA guidelines. English articles published between 2011 to 2021 were included and analysed by descriptive statistics and RevMan 5.4. Quality assessment was assessed with Newcastle-Ottawa scale. There were six studies selected with 322 participants’ data. Trace elements Cu (SMD=-0.13, 95%CI=[-0.99, 0.73], I2=92%, p=0.77), Zn (SMD=-0.38, 95%CI=[-0.81, 0.06], I2=71%, p=0.09), Fe (SMD=0.47, 95%CI=[-1.19, 2.13], I2=97%, p=0.58) and Mn (SMD=0.11, 95%CI=[-0.11, 0.33], I2=0%, p=0.33) levels were not significant. Sensitivity analysis revealed significant Cu level among patients with CHD (SMD=-0.54, 95%CI=[-0.85, -0.22], I2=0%, p=0.0008) and Fe level among the controls (SMD=1.41, 95%CI=[0.08, 2.73], I2=95%, p=0.04). Whereas Co and Cr levels varied according to dietary and smoking behaviours. Overall quality assessment was medium-to-high quality. Elements Cu was found significant in CHD patients and Fe was found significant among the controls, while other findings were inconclusive.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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".