The role of aldosterone inhibitors in cardiac ischemia–reperfusion injury
Bibliographic record
Abstract
Myocardial ischaemia-reperfusion (I/R) injury is a well-known term for exacerbation of cellular destruction and dysfunction after the restoration of blood flow to a previously ischaemic heart. A vast number of studies that have demonstrated that the role of mineralocorticoids in cardiovascular diseases is based on the use of pharmacological mineralocorticoid receptor (MR) antagonists. This review paper aimed to summarize current knowledge on the effects of MR antagonists on myocardial I/R injury as well as postinfarction remodeling. Animal models, predominantly the Langendorff technique and left anterior descending coronary artery occlusion, have confirmed the potency of MR antagonists as preconditioning and postconditioning agents in limiting infarct size and postinfarction remodeling. Several preclinical studies in rodents have established and proved possible mechanisms of cardioprotection by MR antagonists, such as reduction of oxidative stress, reduction of inflammation, and apoptosis, therefore limiting the infarct zone. However, the results of some clinical trials are inconsistent, since they reported no benefit of MR antagonists in acute myocardial infarction. Due to this, further studies and the results of ongoing clinical trials regarding MR antagonist administration in patients with acute myocardial infarction are being awaited with great interest.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".