Survival outcomes and adverse events in patients with chronic kidney disease after coronary artery bypass grafting and percutaneous coronary intervention: a meta-analysis of propensity score-matching studies
Bibliographic record
Abstract
BACKGROUND: The present meta-analysis of propensity score-matching studies aimed to compare the long-term survival outcomes and adverse events associated with coronary artery bypass grafting (CABG) and percutaneous coronary intervention (PCI) in patients with chronic kidney disease (CKD). METHODS: Electronic databases were searched for studies comparing CABG and PCI in patients with CKD. The search period extended to 13 February 2021. The primary outcome was all-cause mortality, and the secondary endpoints included myocardial infarction, revascularization, and stroke. Odds ratios (ORs) and hazard ratios (HRs) with 95% confidence intervals (CIs) were used to express the pooled effect. Study quality was assessed using the Newcastle-Ottawa scale. The analyses were performed using RevMan 5.3. RESULTS: > .05). Subgroup analysis among patients on dialysis yielded similar results. CONCLUSIONS: Our propensity score matching analysis revealed that, based on long-term follow-up outcomes, CABG remains superior to PCI in patients with CKD.
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.
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 | 0.032 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.054 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".