Incidence and Predictors of Outcome in the Treatment of In-Stent Restenosis with Drug-Eluting Balloons, a Real-Life Single-Centre Study
Why this work is in the frame
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Bibliographic record
Abstract
Objectives: To determine the one-year and five-year occurrence and prognosticators of major adverse cardiac events (MACE: composition of all-cause death, myocardial infarction, target vessel revascularization, and vessel thrombosis), mortality, and target lesion revascularization (TLR) in patients with in-stent restenosis (ISR) treated with drug-eluting balloons (DEBs). Background: DEBs have become an emerging therapeutic option for ISR. We report the results of a single-center retrospective study on the treatment of ISR with DEB. Methods: 94 consecutive patients with ISR treated with the paclitaxel-eluting balloon were retrospectively studied between August 2011 and December 2019. Results: The one-year MACE rate was 11.8%, and the five-year MACE rate was 39.8%. The one-year mortality was 5.3%, and the five-year mortality rate was 21.5%. The one-year TLR rate was 4.3%, and the five-year rate was 18.7%. The univariable-Cox proportional hazard models for TLR showed lesion length, and the number of DEBs per vessel is associated with adverse outcomes with H.R. of 1.038 (1.007-1.069) and 4.7 (1.6-13.8), respectively. Conclusion: Our data indicate that at one year, DEBs provide an effective alternative to stenting for in-stent restenosis. Our five-year data, representing one of the longest-term follow-ups of DEB use, demonstrate high rates of MACE. The high five-year MACE reflects all-cause mortality in a high-risk population. This is offset by a reasonable five-year rate of TLR, indicating that DEB provides both short-term and long-term benefits in ISR.
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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 | 0.000 |
| 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) | 0.000 | 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 it