Fetuin-A levels in association with calcific aortic valve disease: A meta-analysis
Bibliographic record
Abstract
Background and aims: Calcific aortic valve disease (CAVD) is a common valvular disease, prevalent particularly within the older age groups. The potential use of biomarkers in diagnosing and assessing the severity of CAVD, in supplementation with imaging techniques, has recently gained momentum within the field of cardiovascular medicine. Therefore, a meta-analysis was performed that assessed the association between the fetuin-A levels, and the presence of CAVD. Methods: PubMed and Cochrane were searched from inception to April 2023. Risk of bias was assessed using the Newcastle-Ottawa scale for cohort studies. Results: This analysis includes a total of 3,280 patients with CAVD, and 7,505 patients as control, resulting in the pooling of 10,785 patients in this meta-analysis. It was observed that the circulating levels of fetuin-A were significantly lowered in patients with CAVD (SMD: -0.20; 95% CI: -0.39, -0.02; P = 0.03). Moreover, the analysis revealed that fetuin-A levels had no significant association with CAVD in patients suffering from kidney disease (SMD: 0.20; 95% CI: -0.46, 0.85; P = 0.56). Conclusion: While initial results demonstrate the potential effectiveness, further research is essential in order to arrive at a robust conclusion regarding the use of fetuin-A as a diagnostic biomarker for calcific aortic valve disease.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.047 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".