Single-Centre Registry Analysis of Patients Who Underwent Percutaneous Coronary Intervention on Their Coronary Bypass Grafts
Bibliographic record
Abstract
Background The study assessed the outcomes of patients undergoing percutaneous coronary intervention (PCI) to bypass grafts, focusing on all-cause mortality and target vessel failure (TVF) rates. Methods A single-centre registry analysis included 364 patients who underwent PCI on coronary bypass grafts between 2008 and 2019. The study analyzed all-cause mortality and TVF, which encompassed target lesion revascularization, target vessel revascularization, and medically treated occluded target graft post-PCI. Results The median age of the patients was 71 years (interquartile range: [IQR] 65-78), with 82.1% being male. Most patients (94.8%) received PCI on saphenous vein grafts, and the median graft age was 13.0 years (IQR: 8.4-17.6). Drug-eluting stents were used more frequently (54.4%) than bare-metal stents (45.6%), with a median stent diameter of 3.5 mm (IQR: 3-4) and length of 19 mm (IQR: 18-28). Outcome differences were not significant for PCI sites (aorto-ostial, graft body, anastomosis), use of drug-eluting stents, or use of protection devices. The 1-year mortality rate was 3.3%, whereas the combined rate of TVF or death was 20.3%. After 5 years, the mortality rate increased to 14.9%, and the combined TVF or death rate rose to 40.3%. Multivariable analyses revealed that chronic kidney disease was independently associated with mortality (hazard ratio [HR] 1.74, 95% confidence interval [CI] 1.16-2.61, P = 0.007), whereas hypertension (HR 2.42, 95% CI 1.32-4.42, P = 0.004) and increased stent length (HR 1.01, 95% CI 1.00-1.02, P = 0.007) were independently associated with the TVF-or-mortality outcome. Conclusions Patients undergoing PCI to bypass grafts experience considerable adverse outcomes over a 5-year period, highlighting the need for further strategies in managing this high-risk population.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".