The Technique of Angioplasty and Stent Placement in Acute Ischemic Stroke Therapy
Bibliographic record
Abstract
Stroke is a second leading cause of death and disability in both developed and developing countries. 8-10% of ischemic strokes are caused by stenosis consequent to intracranial atherosclerotic disease. A growing body of evidence suggests that an aggressive approach may be indicated for patients with intracranial stenosis in the face of persistent symptoms despite adequate medical management, as the incidence of stroke or death in such situations is greater than 50%. By comparison, patients who fail medical management and intravenous thrombolysis, the risk of neurological complications from angioplasty, stenting, or both together, has been reported as 0% to 28%. The technical success rates for immediate, delayed and rescue angioplasty are very good (71-100%). Stenting is an option following angioplasty of a stenosed vessel and in case of embolic strokes where angioplasty alone produces only a temporary recanalizing effect. The rate of stroke and death from intracranial angioplasty and stenting is up to 10%, which is favorable when taking into consideration the risks of failed medical management. Currently, endovascular intervention is usually undertaken when medical management fails. Studies demonstrate angioplasty and stenting to be safe and effective. Technical success rate of angioplasty and stenting is up to 98-99%. In this review, we address the indications for intracranial angioplasty and stenting and provide a reasonably detailed account for readers who perform these procedures. We will also address the potential complications that might arise during intervention and provide practical tips towards successful resolution. doi:10.4021/jnr31w
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 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) | 0.000 | 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 | 0.001 |
| 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".