The Impact of Target Vessel Diameter on the Outcomes of Chronic Total Occlusion Percutaneous Coronary Intervention: Insights From the PROGRESS‐CTO Registry
Bibliographic record
Abstract
BACKGROUND: The impact of target vessel diameter on outcomes of chronic total occlusion (CTO) percutaneous coronary intervention (PCI) has received limited study. AIM: To compare the impact of target vessel diameter on CTO PCI outcomes. METHODS: We examined the association of vessel diameter with clinical, angiographic characteristics, and procedural outcomes of CTO-PCI in a large multicenter registry. The CTO vessels were classified as small (≤ 2.75 mm), medium (2.76-3.00 mm), and large (> 3.00 mm) diameter. RESULTS: Among 13,423 patients who underwent CTO-PCI at 47 centers between 2012 and 2024, the target CTO vessel was small in 4858 (36%), medium in 5393 (40%), and large in 3172 (24%). Compared with patients who had medium and large CTO target vessels, those who had small vessels were older and had a higher prevalence of diabetes, hypertension, dyslipidemia, and peripheral arterial disease. Large target vessel diameter CTOs had more complex angiographic characteristics such as higher J-CTO scores, longer lesion length, and more complex angiographic characteristics. Compared with CTO PCI of small and large vessel patients, medium vessel patients had higher technical (p = 0.008) and procedural (p = 0.010) success. The incidence of perforation was higher in large-diameter vessels. In multivariable logistic regression using restricted cubic spline analysis, a vessel diameter of 2.75-3.00 mm was associated with higher technical (OR 2.05 95% CI 1.12-3.76; p < 0.001) and procedural (OR 2.48 95% CI 1.49-4.13; p < 0.001) success compared with a vessel diameter of less than 2.75 or greater than 3.00 mm. CONCLUSIONS: Large and small CTO target vessels were associated with lower technical and procedural success compared with medium-sized vessels.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".