Managing Common Co-morbidities in Heart Failure
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
Heart failure increases in prevalence with age and is usually associated with various cardiac and non-cardiac comorbidities. For common coexisting conditions such as renal dysfunction, anemia and type 2 diabetes mellitus, important pathophysiologic links have been implicated between cardiac dysfunction and the underlying condition. Indeed, the number and severity of comorbidities in the setting of heart failure is an important driver of prognosis. By targeting the management of coexisting diseases, it may be possible to improve functional capacity, quality of life and perhaps even overall mortality in heart failure patients. Recent clinical trial data has provided insights into cardio-renal interactions in acute heart failure, the impact of iron replacement therapy in iron deficient heart failure patients, and the role of pharmacologic therapies to prevent heart failure related events in high risk patients with type 2 diabetes.
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) | 0.001 | 0.000 |
| 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) | 0.001 | 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