Cardiac Disease in Chronic Kidney Disease: Current Understandings and Opportunities for Change
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
Cardiovascular disease (CVD) is prevalent in patients with kidney disease: in populations prior to dialysis, on dialysis and after transplantation. Publications over the last decade have focused on this, and more recently, patients with cardiac disease are now recognized as being at increased risk in the presence of even mild kidney dysfunction. The presence of both traditional and non-traditional risk factors contributes to this overwhelming burden of cardiovascular disease in patients with chronic kidney disease (CKD). Recent studies have focused on the impact of anemia and disorders of mineral metabolism on CVD outcomes, in the context of inflammation and evidence of cytokine activation. Cross-sectional and prospective observational studies have led to improved understanding, and generated novel hypotheses. To date, no clinical trial has determined the positive impact of interventions targeted at these novel risk factors. This overview describes the current state of knowledge and emphasizes the interplay between CVD and CKD as two aspects of a set of pathophysiological processes, which impact on patient outcomes.
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) | 0.000 | 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