Verapamil eluting stents as a possible treatment for vasospasm after subarachnoid hemorrhage
Bibliographic record
Abstract
OBJECTIVE: The only pharmacologic prophylaxis for cerebral vasospasm after subarachnoid hemorrhage is oral nimodipine. A novel way to mitigate this risk may be to design a drug eluting stent that elutes verapamil over the time period typically associated with vasospasm. In this study, we explore different methods of coating nitinol stents with a bioabsorbable polymer and determine the release profile of various verapamil coated stents for the potential treatment of vasospasm. METHODS: Nitinol stents were coated with different concentrations of poly(lactic acid-co-glycolic acid) (PLGA) in chloroform solution and using three coating techniques: dip coating, spin coating, and electrospinning. Morphology of the coatings were studied with scanning electron microscopy. 12 verapamil eluting stents were then prepared using different verapamil concentrations and coatings with different numbers of layers. Drug release behaviors were studied using UV spectroscopy for 21 days. RESULTS: Electrospinning at 20% w/v resulted in a smooth uniform coating without significant surface irregularities, and may be the most effective technique to coat stents. Stents with a single layer of PLGA/verapamil coating showed a two phase release profile (initial burst release followed by a slow rate of release) whereas stents with a bilayer coating showed a lower level of initial release followed by a slower sustained release phase. CONCLUSIONS: Development of verapamil eluting stents that elute drug over the time course typical of cerebral vasospasm, and for either immediate or prophylactic treatment, is technically feasible. Further in vitro and in vivo studies are required to determine whether this can improve the outcome of patients after subarachnoid hemorrhage.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".