D-35 | Ranolazine and Chronic Total Occlusion Percutaneous Coronary Intervention
Bibliographic record
Abstract
The association between ranolazine use and the outcomes of chronic total occlusion (CTO) percutaneous coronary intervention (PCI) has not been investigated. We examined 11,491 CTO PCIs (11,478 patients) that were performed at 41 US and non-US centers between 2012 and 2023 in the PROGRESS CTO registry. During the study period, 1,720 (15%) patients undergoing CTO PCI were using ranolazine on baseline. Patients receiving ranolazine had a higher prevalence of diabetes, hypertension, dyslipidemia, family history of coronary artery disease, prior history of PCI, coronary artery bypass graft surgery, cerebrovascular and peripheral arterial disease. They had higher J-CTO (2.85 vs 2.31; p<0.001) and PROGRESS-CTO (1.45 vs 1.21; p<0.001) scores, longer lesion length and higher prevalence of proximal cap ambiguity, blunt/no stump, moderate to severe calcification and proximal tortuosity. Their procedure (139.00 vs 108.00 min; p<0.001) and fluoroscopy (53.00 vs 40.00 min; p<0.001) times were longer. Technical (83.7% vs 87.8%; p<0.001) and procedural (81.4% vs 86.6%; p<0.001) success were lower in patients using ranolazine, while the incidence of major adverse cardiovascular events (MACE) was higher (3.2% vs 1.8%; p<0.001) due to higher in-hospital mortality (0.8% vs 0.4%; p=0.051), acute myocardial infarction (0.9% vs 0.4%; p=0.006), repeat PCI (0.5% vs 0.1%; p=0.006), stroke (0.4% vs 0.1%; p=0.008) and perforation (5.8% vs 4.6%; p=0.030). In multivariable analysis, ranolazine was associated with higher MACE (odds ratio [OR] 2.21; 95% CI 1.44 – 3.30; p<0.001), but was not associated with technical success (OR 1.00; 95% CI 0.82 – 1.22; p>0.9). Patients undergoing CTO PCI who use ranolazine have more comorbidities, more complex lesions, lower technical success, and higher in-hospital MACE.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".