Randomized Trial of <sup>90</sup> Sr/ <sup>90</sup> Y β-Radiation Versus Placebo Control for Treatment of In-Stent Restenosis
Bibliographic record
Abstract
BACKGROUND: After conventional treatment of in-stent restenosis, the incidence of recurrent clinical restenosis may approach 40%. We report the first multicenter, blinded, and randomized trial of intracoronary radiation with the use of a 90Sr/90Y beta-source for the treatment of in-stent restenosis. METHODS AND RESULTS: After successful catheter-based treatment of in-stent restenosis, 476 patients were randomly assigned to receive an intracoronary catheter containing either 90Sr/90Y (n=244) or placebo (n=232) sources. The prescribed dose 2 mm from the center of the source was 18.4 Gy for vessels between 2.70 and 3.35 mm in diameter and 23.0 Gy for vessels between 3.36 and 4.0 mm. The primary end point, ie, clinically driven target-vessel revascularization by 8 months, was observed in 56 (26.8%) of the patients assigned to placebo and 39 (17.0%) of the patients assigned to radiation (P=0.015). The incidence of the composite including death, myocardial infarction, and target-vessel revascularization was observed in 60 (28.7%) of the patients assigned to placebo and 44 (19.1%) of the patients assigned to radiation (P=0.024). Binary 8-month angiographic restenosis (> or =50% diameter stenosis) within the entire segment treated with radiation was reduced from 45.2% in the placebo-treated patients to 28.8% in the 90Sr/90Y-treated patients (P=0.001). Stent thromboses occurred in 1 patient assigned to placebo <24 hours after the procedure and in 1 patient assigned to 90Sr/90Y at day 244. CONCLUSIONS: The results of this study demonstrated that beta-radiation using 90Sr/90Y is both safe and effective for preventing recurrence in patients with in-stent restenosis.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".