Improving Prognosis Estimation in Patients with Heart Failure and the Cardiorenal Syndrome
Bibliographic record
Abstract
The coexistence of heart failure and renal dysfunction constitutes the "cardiorenal syndrome" which is increasingly recognized as a marker of poor prognosis. Patients with cardiorenal dysfunction constitute a large and heterogeneous group where individuals can have markedly different outcomes and disease courses. Thus, the determination of prognosis in this high risk group of patients may pose challenges for clinicians and for researchers alike. In this paper, we discuss the cardiorenal syndrome as it pertains to the patient with heart failure and considerations for further refining prognosis and outcomes in patients with heart failure and renal dysfunction. Conventional assessments of left ventricular function, renal clearance, and functional status can be complemented with identification of coexistent comorbidities, medication needs, microalbuminuria, anemia, biomarker levels, and pulmonary pressures to derive additional prognostic data that can aid management and provide future research directions for this challenging patient group.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".