Guidelines on models of diabetic heart disease
Bibliographic record
Abstract
Diabetes is a major risk factor for cardiovascular diseases, including diabetic cardiomyopathy, atherosclerosis, myocardial infarction, and heart failure. As cardiovascular disease represents the number one cause of death in people with diabetes, there has been a major emphasis on understanding the mechanisms by which diabetes promotes cardiovascular disease, and how antidiabetic therapies impact diabetic heart disease. With a wide array of models to study diabetes (both type 1 and type 2), the field has made major progress in answering these questions. However, each model has its own inherent limitations. Therefore, the purpose of this guidelines document is to provide the field with information on which aspects of cardiovascular disease in the human diabetic population are most accurately reproduced by the available models. This review aims to emphasize the advantages and disadvantages of each model, and to highlight the practical challenges and technical considerations involved. We will review the preclinical animal models of diabetes (based on their method of induction), appraise models of diabetes-related atherosclerosis and heart failure, and discuss in vitro models of diabetic heart disease. These guidelines will allow researchers to select the appropriate model of diabetic heart disease, depending on the specific research question being addressed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".