Atrial Fibrillation and Congestive Heart Failure: Specific Considerations at the Intersection of Two Common and Important Cardiac Disease Sets
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
Atrial fibrillation (AF) and congestive heart failure (CHF) are two increasingly common cardiac disorders with a growing prevalence in the overall population. Improved treatment of acute medical conditions has increased the incidence of these cardiac disorders. AF and CHF have similar epidemiologic characteristics and adversely affect quality of life and life expectancy of affected patients. CHF predisposes to AF, and AF may worsen the prognosis of CHF. The relevant literature was intensively reviewed with emphasis on aspects at the intersection of both disease sets. Recent advances in basic research have provided a more in-depth view of changes promoting the occurrence of AF in CHF. Data from clinical trials have provided means to improve medical treatment of AF. Precautions must be taken for specific CHF-related side effects, such as torsades de pointes tachycardia, when treating AF. The specific electrophysiologic basis of AF associated with CHF may provide targets for improved treatment modalities. New treatment approaches, both pharmacologic and nonpharmacologic, as well as the results of ongoing controlled clinical studies are likely to greatly alter AF therapy over the next 5 to 10 years in patients with CHF.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| 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