Bibliographic record
Abstract
The dramatic increase in the prevalence of obesity and its strong association with cardiovascular disease have resulted in unprecedented interest in understanding the effects of obesity on the cardiovascular system. A consistent, but puzzling clinical observation is that obesity confers an increased susceptibility to the development of cardiac disease, while at the same time affording protection against subsequent mortality (termed the obesity paradox). In this review we focus on evidence available from human and animal model studies and summarize the ways in which obesity can influence structure and function of the heart. We also review current hypotheses regarding mechanisms linking obesity and various aspects of cardiac remodeling. There is currently great interest in the role of adipokines, factors secreted from adipose tissue, and their role in the numerous cardiovascular complications of obesity. Here we focus on the role of leptin and the emerging promise of adiponectin as a cardioprotective agent. The challenge of understanding the association between obesity and heart failure is complicated by the multifaceted interplay between various hemodynamic, metabolic, and other physiological factors that ultimately impact the myocardium. Furthermore, the end result of obesity-associated changes in the myocardial structure and function may vary at distinct stages in the progression of remodeling, may depend on the individual pathophysiology of heart failure, and may even remain undetected for decades before clinical manifestation. Here we summarize our current knowledge of this complex yet intriguing topic.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".