Epicardial Adipose Tissue, Adiponectin and Leptin: A Potential Source of Cardiovascular Risk in Chronic Kidney Disease
Bibliographic record
Abstract
The importance of cardiometabolic factors in the inception and progression of atherosclerotic cardiovascular disease is increasingly being recognized. Beyond diabetes mellitus and metabolic syndrome, other factors may be responsible in patients with chronic kidney disease (CKD) for the high prevalence of cardiovascular disease, which is estimated to be 5- to 20-fold higher than in the general population. Although undefined uremic toxins are often blamed for part of the increased risk, visceral adipose tissue, and in particular epicardial adipose tissue (EAT), have been the focus of intense research in the past two decades. In fact, several lines of evidence suggest their involvement in atherosclerosis development and its complications. EAT may promote atherosclerosis through paracrine and endocrine pathways exerted via the secretion of adipocytokines such as adiponectin and leptin. In this article we review the current knowledge of the impact of EAT on cardiovascular outcomes in the general population and in patients with CKD. Special reference will be made to adiponectin and leptin as possible mediators of the increased cardiovascular risk linked with EAT.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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".