Angiographic Safety and Efficacy of the ReSolv Flow-Diverting Stent in a Rabbit Model
Bibliographic record
Abstract
Background Bioresorbable polymer-based flow-diverting stents have potential benefits over existing metal devices. This study aimed to evaluate the safety and efficacy of the novel ReSolv device, which is a primarily polymer-based flow-diverting stent, using the in vivo rabbit sidewall saccular aneurysm model. Methods ReSolv stents were deployed in 14 New Zealand White rabbits that had undergone aneurysm creation procedures. Animals were allocated to follow-up time points of 1, 3, 6, 9, 12, 16, or 18 months. Angiographic images were evaluated by an independent neurointerventionalist blinded to follow-up time points for (1) in-stent stenosis, (2) parent vessel and jailed side branch patency, (3) wall apposition, and (4) aneurysm occlusion using the Raymond-Roy Occlusion Classification (RROC), O’Kelly Marotta grading scale, and the 4F flow diversion predictive score. Primary efficacy outcome was defined as RROC Class I or II. Results At a median follow-up time of 7.5 months, parent vessel (14/14) and jailed side (33/33) branches were patent in all cases. There was no development of thrombus on the stent or cases of significant in-stent stenosis, and all stents had good wall apposition. Adequate occlusion was found in 85.7% ( n = 12) of animals, including an RROC Class I in 64.3% ( n = 9) and RROC Class II in 21.4% ( n = 3). Conclusions The ReSolv stent shows encouraging angiographic safety and efficacy outcomes after placement in a rabbit sidewall saccular aneurysm model. Longer term studies are ongoing to determine eventual fate of the aneurysm, parent vessel, and jailed side branches after absorption of the polymer component of the stent.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".