Decreased risk of stent fracture‐related restenosis between paclitaxel‐eluting stents and sirolimus eluting stents: Results of long‐term follow‐up
Bibliographic record
Abstract
OBJECTIVE: To compare the outcomes between paclitaxel-eluting stents (PES) and sirolimus-eluting stents (SES) for the treatment of drug-eluting stent (DES) fracture. BACKGROUND: DES fracture is considered as an important predictor of in-stent restenosis (ISR). However, little data are available evaluating the optimal treatment for this complication of coronary stenting. METHODS: From January 1, 2004 to December 31, 2008, patients with DES ISR treated with a second DES were identified and evaluated for stent fracture. Stent fracture was defined by the presence of strut separation in multiple angiographic projections, assessed by two independent reviewers. Target lesion revascularization (TLR) at 6 and 12 months were the primary end points. RESULTS: Of 131 lesions with DES ISR treated with a second DES, we found 24 patients (24 lesions, 18.2%) with angiographically confirmed stent fracture. Of these, 20 patients (20 lesions) treated with either PES (n = 11/55%) or SES (n = 9/45%) were included in the study. TLR at 6 months occurred in 9% of patients treated with PES and 22% of those treated with SES (P = 0.41). After 12 months, TLR was 9% and 55.5%, respectively (P = 0.024). CONCLUSIONS: This study demonstrates a high incidence of stent fracture in patients presenting with DES ISR in need of further treatment with another DES. The suggested association between treatment of stent fracture-associated DES ISR with PES as compared with SES, and better long-term outcomes, is in need of confirmation by larger prospective registries and randomized trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".