Treatment of coronary lesions with a novel crystalline sirolimus-coated balloon
Bibliographic record
Abstract
Background: There is mounting data supporting the use of drug-coated balloons (DCB) not only for treatment of in-stent restenosis (ISR), but also in native coronary artery disease. So far, paclitaxel-coated balloons represented the mainstay DCBs. The SeQuent® crystalline sirolimus-coated balloon (SCB) (B.Braun Medical Inc, Germany) represents a novel DCB, which allows a sustained release of the limus-drug. We evaluated its performance in an all-comer cohort, including complex coronary lesions. Methods: Consecutive patients treated with the SeQuent® SCB were analyzed from the prospective SIROOP registry (NCT04988685). We assessed clinical outcomes, including major adverse cardiovascular events (MACE), target lesion revascularization (TLR), target vessel myocardial infarction (TV-MI) and cardiovascular death. Angiograms and outcomes were independently adjudicated. Results: From March 2021 to March 2023, we enrolled 126 patients and lesions, of which 100 (79%) treated using a "DCB-only" strategy and 26 (21%) with a hybrid approach (DES + DCB). The mean age was 68 ± 10 years, 48 (38%) patients had an acute coronary syndrome. Regarding lesion characteristics, ISR was treated in 27 (21%), 11 (9%) underwent CTO-PCI and 59 (47%) of the vessels were moderate to severe calcified. Procedural success rate was 100%. At a median follow-up time of 12.7 (IQR 12; 14.2) months, MACE occurred in 5 patients (4.3%). No acute vessel closure was observed. Conclusions: Our data indicates promising outcomes following treatment with this novel crystalline SCB in an all-comer cohort with complex coronary lesions. These results require further investigation with randomized trials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".