Overview of Cardiac Arrhythmias and Treatment Strategies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Maintenance of normal cardiac rhythm requires coordinated activity of ion channels and transporters that allow well-ordered propagation of electrical impulses across the myocardium. Disruptions in this orderly process provoke cardiac arrhythmias that may be lethal in some patients. Risk of common acquired arrhythmias is increased markedly when structural heart disease caused by myocardial infarction (due to fibrotic scar formation) or left ventricular dysfunction is present. Genetic polymorphisms influence structure or excitability of the myocardial substrate, which increases vulnerability or risk of arrhythmias in patients. Similarly, genetic polymorphisms of drug-metabolizing enzymes give rise to distinct subgroups within the population that affect specific drug biotransformation reactions. Nonetheless, identification of triggers involved in initiation or maintenance of cardiac arrhythmias remains a major challenge. Herein, we provide an overview of knowledge regarding physiopathology of inherited and acquired cardiac arrhythmias along with a summary of treatments (pharmacologic or non-pharmacologic) used to limit their effect on morbidity and potential mortality. Improved understanding of molecular and cellular aspects of arrhythmogenesis and more epidemiologic studies (for a more accurate portrait of incidence and prevalence) are crucial for development of novel treatments and for management of cardiac arrhythmias and their consequences in patients, as their incidence is increasing worldwide.
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.
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) | 0.003 | 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 it