Debulking does not benefit patients undergoing intracoronary beta‐radiation therapy for in‐stent restenosis: Insights from the START trial
Bibliographic record
Abstract
Intracoronary brachytherapy has become the current treatment of choice for patients with in-stent restenosis (ISR). The aim of the present study was to determine whether plaque extraction using debulking techniques prior to brachytherapy would improve the outcomes of patients with ISR. Patients enrolled into the START (n = 476) and START-40 (n = 205) trials were divided into four subgroups according to their treatment assignments: debulking-radiation, debulking-placebo, balloon angioplasty (BA) radiation, and BA placebo. Patients were further divided according to their ISR lesion length: all lesions, > 15 mm, and > 19 mm. Restenosis rates were higher in placebo, nonradiated lesions undergoing debulking (52.7%) vs. BA alone (38.5%; P = 0.04). Postprocedural minimal lumen diameter (MLD) was similar among the subgroups. Outcomes were similar between debulking and BA within each therapeutic arm. MLD after debulking radiation was greater in patients with ISR > 15 mm (post-MLD was 1.9 vs. 1.7 mm; P = 0.06) but not in the placebo. Debulking radiation patients had greater MLD at follow-up, but restenosis (23.5% after debulking vs. 32.7% BA alone) and late loss (0.3 mm in both subgroups) were not statistically different. There was a trend toward higher mortality among debulked patients (3.7%) compared to BA alone (0.8%). In patients with ISR > 19 mm, four patients died following debulking radiation as compared to no death after BA (P = 0.05). Our results do not support the strategy of plaque extraction prior to intracoronary beta-radiation for ISR.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".