Stent Ablation by Rotational Atherectomy for Management of Resistant Lesions within and across the Stent Struts in Coronary Arteries
Bibliographic record
Abstract
Background: Non-dilatable stent underexpansion has limited treatment options. Stent ablation by rotational atherectomy (RA) for the management of non-dilatable coronary stents is an off-label strategy. The principle of stent ablation by RA of underexpanded stent relies on modification of both stent and underlying calcium. This study aims to describe and compare the use of RA for non-dilatable lesions in two anatomical categories: group 1 (within the stent struts) and group 2 (across the stent struts). Methods: A total of seven patients who had undergone stent ablation by RA were analysed. Indications for revascularisation were acute coronary syndrome or chronic stable angina. Two groups are described: RA within underexpanded stents (group 1) and across the stent struts (across stented bifurcation; group 2). Results: The burr:artery ratio was 0.6 ± 0.1 in group 1 and 0.5 in group 2 (p=0.24). The maximum rotational speed was 154,400 ± 2,500 and 155,000 rpm in the two groups. The total number of RA runs was 3.6 ± 0.90 in group 1 and 7.0 ± 2.8 in group 2, respectively, p=0.04. Procedural success was achieved in all cases with no complications. Conclusion: RA is a feasible bailout option for resistant non-dilatable lesions within and across the stent struts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".