Survival After Coronary Revascularization Among Patients With Kidney Disease
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
BACKGROUND: The optimal approach to revascularization in patients with kidney disease has not been determined. We studied survival by treatment group (CABG, percutaneous coronary intervention [PCI], or no revascularization) for patients with 3 categories of kidney function: dialysis-dependent kidney disease, non-dialysis-dependent kidney disease, and a reference group (serum creatinine <2.3 mg/dL). METHODS AND RESULTS: Data were derived from the Alberta Provincial Project for Outcomes Assessment in Coronary Heart Disease (APPROACH), which captures information on all patients undergoing cardiac catheterization in Alberta, Canada. Characteristics and patient survival in 662 dialysis patients (1.6%) and 750 non-dialysis-dependent kidney disease patients (1.8%) were compared with the remainder of the 40,374 patients (96.6%). For the reference group, the adjusted 8-year survival rates for CABG, PCI, and no revascularization (NR) were 85.5%, 80.4%, and 72.3%, respectively (P<0.001 for CABG versus NR; P<0.001 for PCI versus NR). Adjusted survival rates were 45.9% for CABG, 32.7% for PCI, and 29.7% for NR in the nondialysis kidney disease group (P<0.001 for CABG versus NR; P=0.48 for PCI versus NR) and 44.8% for CABG, 41.2% for PCI, and 30.4% for NR in the dialysis group (P=0.003 for CABG versus NR; P=0.03 for PCI versus NR). CONCLUSIONS: Compared with no revascularization, CABG was associated with better survival in all categories of kidney function. PCI was also associated with a lower risk of death than no revascularization in reference patients and dialysis-dependent kidney disease patients but not in patients with non-dialysis-dependent kidney disease. The presence of kidney disease or dependence on dialysis should not be a deterrent to revascularization, particularly with CABG.
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 | 0.001 |
| 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