Lesion Complexity and Procedural Outcomes Associated With Ostial Chronic Total Occlusions: Insights From the PROGRESS-CTO Registry
Bibliographic record
Abstract
OBJECTIVES: Ostial CTOs can be challenging to revascularize. We aim to describe the outcomes of ostial chronic total occlusion (CTO) percutaneous coronary intervention (PCI). METHODS: We examined the clinical and angiographic characteristics and procedural outcomes of 8788 CTO PCIs performed at 35 US and non-US centers between 2012 and 2022. In-hospital major adverse cardiac events (MACE) included death, myocardial infarction, urgent repeat target-vessel revascularization, tamponade requiring pericardiocentesis or surgery, and stroke. RESULTS: Ostial CTOs constituted 12% of all CTOs. Patients with ostial CTOs had higher J-CTO score (2.9 ± 1.2 vs 2.3 ± 1.3; P less than .01). Ostial CTO PCI had lower technical (82% vs. 86%; P less than .01) and procedural (81% vs. 85%; P less than .01) success rates compared with non-ostial CTO PCI. Ostial location was not independently associated with technical success (OR 1.03, CI 95% 0.83-1.29 P =.73). Ostial CTO PCI had a trend towards higher incidence of MACE (2.6% vs. 1.8%; P =.06), driven by higher incidence of in-hospital death (0.9% vs 0.3% P less than.01) and stroke (0.5% vs 0.1% P less than .01). Ostial lesions required more often use of the retrograde approach (30% vs 9%; P less than .01). Ostial CTO PCI required longer procedure time (149 [103,204] vs 110 [72,160] min; P less than .01) and higher air kerma radiation dose (2.3 [1.3, 3.6] vs 2.0 [1.1, 3.5] Gray; P less than .01). CONCLUSIONS: Ostial CTOs are associated with higher lesion complexity and lower technical and procedural success rates. CTO PCI of ostial lesions is associated with frequent need for retrograde crossing, higher incidence of death and stroke, longer procedure time and higher radiation dose.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".