The Role of Adiponectin and Leptin in Fibro-Calcific Aortic Valve Disease: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Fibro-calcific aortic valve disease (FCAVD) is a progressive disorder characterized by the thickening and calcification of the aortic valve, eventually leading to aortic stenosis. Adiponectin and leptin, known for their anti-inflammatory and proinflammatory properties, respectively, have been implicated in cardiovascular diseases, but their associations with FCAVD are controversial. This meta-analysis aims to evaluate the relationships between adiponectin and leptin levels and FCAVD, particularly in patients with severe aortic stenosis (AS). Methods: A systematic search was conducted across the PubMed, Scopus, and Web of Science databases to identify studies on adiponectin and leptin levels in FCAVD. The methodological quality of each study was assessed using the Newcastle–Ottawa Scale. Standardized mean differences (SMDs) and 95% confidence intervals (CIs) were calculated, and publication bias was evaluated using Egger’s test and funnel plots. Results: Out of 191 articles identified, 10 studies involving 2360 patients (989 with FCAVD and 1371 controls) were included. The analysis suggested trends in the associations of lower adiponectin levels (SMD = −0.143, 95% CI: −0.344, 0.057, p = 0.161) and higher leptin levels (SMD = 0.175, 95% CI: −0.045, 0.395, p = 0.119) with FCAVD. The association remained a trend for low adiponectin but showed a significant correlation with high leptin in severe AS patients (SMD = 0.29, 95% CI: 0.036, 0.543, p = 0.025). Conclusion: This meta-analysis indicates a potential association between elevated leptin levels and severe aortic stenosis, while the relationship with adiponectin levels remains inconclusive. These findings highlight the need for further and dedicated research to clarify the roles of these adipokines in the pathogenesis of FCAVD and their potential roles as biomarkers for disease progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.007 | 0.006 |
| Bibliometrics | 0.001 | 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".