Drug-coated versus conventional balloons to improve recanalization of a coronary chronic total occlusion after failed attempt
Bibliographic record
Abstract
ABSTRACT Background Chronic total occlusion (CTO) plaque modification (CTO-PM) is often used for unsuccessful CTO interventions. Methods Multicenter, prospective study including consecutive patients with failed CTO recanalization. At the end of the failed procedure, patients received either conventional (CB) or drug-coated balloon (DCB) or at the operator’s discretion for CTO-PM and underwent new attempt of CTO recanalization ∼3 months later. Results A total of 55 patients were enrolled (DCB: 22; CB 33), with a median age of 66 years. Median J-score was 3 and CCS angina class III-IV was present in 40% of the patients. After the first CTO-PCI attempt no in hospital cardiac deaths were registered, with 3.6% rates of in-hospital myocardial infarction. The success rate of the second CTP PCI attempt was 86.8%, with periprocedural complication rate of 5.7% and without difference between DCB and CB groups. Compared with CB, in the DCB group, the second CTO-PCI required a shorter median fluoroscopy time (33 vs 60min, p<0.001), lower contrast volume (170 vs 321cc, p<0.001) and lower radiation dose (1.7 vs 3.3Gy, p<0.001). At 1-year follow up outcomes were comparable between the 2 strategies, target lesion failure occurred in 5.7% and major adverse cardiovascular events in 11.2%. Conclusions PM after CTO recanalization failure is safe and warrants high success rates when 2 nd attempt is performed. A DCB strategy for CTO-PM does not seem to ensure higher success or better clinical outcomes, but its use was associated with simpler staged procedures.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".