Dipyridamole and vascular healing following stent implantation
Bibliographic record
Abstract
Introduction Patients undergoing coronary stent implantation incur a 2% annual rate of adverse events, largely driven by in-stent restenosis (ISR) due to neointimal (NI) tissue proliferation, a process in which smooth muscle cell (SMC) biology may play a central role. Dipyridamole (DP) is an approved therapeutic agent with data supporting improved vascular patency rates. Pre-clinical data supports that DP may enact its vasculoprotective effects via adenosine receptor-A2B (ADOR-A2B). We sought to evaluate the efficacy of DP to mitigate ISR in a pre-clinical rabbit stent model. Methods & Results 24 New Zealand White Rabbits were divided into two cohorts—non-atherosclerosis and atherosclerosis (n = 12/cohort, 6 male and 6 female). Following stent implantation, rabbits were randomized 1:1 to control or oral dipyridamole therapy for 6 weeks followed by optical coherence tomography (OCT) and histology assessment of NI burden and stent strut healing. Compared to control, DP demonstrated a 16.6% relative reduction in NI volume (14.7 ± 0.8% vs. 12.5 ± 0.4%, p = 0.03) and a 36.2% relative increase in optimally healed stent struts (37.8 ± 2.8% vs. 54.6 ± 2.5%, p < 0.0001). Atherosclerosis demonstrated attenuated effect with no difference in NI burden (15.2 ± 1.0% vs. 16.9 ± 0.8%, p = 0.22) and only a 14.2% relative increase in strut healing (68.3 ± 4.1% vs. 78.7 ± 2.5%, p = 0.02). DP treated rabbits had a 44.6% (p = 0.045) relative reduction in NI SMC content. In vitro assessment of DP and coronary artery SMCs yielded dose-dependent reduction in SMC migration and proliferation. Selective small molecule antagonism of ADOR-A2B abrogated the effects of DP on SMC proliferation. DP modulated SMC phenotypic switching with ADOR-A2B siRNA knockdown supporting its role in the observed effects. Conclusion Dipyridamole reduces NI proliferation and improves stent healing in a preclinical model of stent implantation with conventional antiplatelets. Atherosclerosis attenuates the observed effect. Clinical trials of DP as an adjunctive agent may be warranted to evaluate for clinical efficacy in stent outcomes.
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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 | 0.000 | 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".