Inadvertent Stent Retriever Detachment: A Multicenter Case Series and Review of Device Experience FDA Reports
Bibliographic record
Abstract
Mechanical thrombectomy using retrievable stents or stent retriever devices has become the mainstay of intra-arterial therapy for acute ischemic stroke. The recent publication of a series of positive trials supporting intra-arterial therapy as standard of care for the treatment of large vessel occlusion will likely further increase stent retriever use. Rarely, premature stent detachment during thrombectomy may be encountered. In our multicenter case series, we found a rate of detachment of less than 1% (n = 7/1,067), and all were first-generation Solitaire FR devices. A review of the US Food and Drug Administration database of device experience yielded 90 individual adverse reports of detachment. There were 82, 1 and 7 detachments of Solitaire FR (first generation), Solitaire FR2 (second generation) and Trevo devices, respectively. We conclude with a brief overview of the technical and procedural considerations which may be helpful in avoiding this rare complication.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".