Management of patients with end-stage renal disease
Bibliographic record
Abstract
PURPOSE OF REVIEW: Coronary artery disease is common in patients with end-stage renal disease (ESRD) on hemodialysis. ESRD patients are prone to atherosclerosis and are likely to present with advanced CAD requiring coronary artery bypass graft surgery (CABG) or percutaneous coronary intervention (PCI). RECENT FINDINGS: Individual observational studies and aggregated results comparing PCI to CABG have shown an increased risk of early postoperative mortality in the CABG group followed by a decrease in late mortality and cardiovascular events. Drug eluting stents are preferred to bare metal stents in patients undergoing PCI. Bilateral versus single internal thoracic arterial grafting strategies showed no difference in survival, freedom from cardiac death or freedom from cardiac events. There was no clear survival advantage to off-pump CABG over on-pump CABG in ESRD patients. Evidence to support either CABG or PCI was limited to retrospective observational studies that were at risk for treatment allocation bias. SUMMARY: CABG carries an upfront risk of increased perioperative mortality while demonstrating late survival benefit compared with PCI. Thus, in the context of balancing these competing risks and benefits, deciding on the most appropriate treatment in this high-risk cohort is challenging. Comprehensive patient evaluation by a multidisciplinary team is strongly recommended.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".