Cardiac Disease in Chronic Kidney Disease: Current Understandings and Opportunities for Change
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.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".