Intraprocedural predictors of post-stent retriever thrombectomy subarachnoid hemorrhage in middle cerebral artery stroke
Bibliographic record
Abstract
BACKGROUND: Stent retriever thrombectomy (SRT) in acute thromboembolic stroke can result in post-thrombectomy subarachnoid hemorrhage (PTSAH). Intraprocedural findings associated with PTSAH are not well defined. OBJECTIVE: To identify angiographic findings and procedural factors during SRT that are associated with PTSAH. MATERIALS AND METHODS: This was a retrospective, observational cohort study of consecutive patients with middle cerebral artery (MCA) acute ischemic stroke treated with SRT. Inclusion criteria were: (1) age ≥18 years; (2) thromboembolic occlusion of the MCA; (3) at least one stent retriever pass beginning in an M2 branch; (4) postprocedural CT or MRI scan within 24 hours; (5) non-enhanced CT Alberta Stroke Program Early CT Score >5. Exclusion criteria included multi-territory stroke before SRT. RESULTS: Eighty-five patients were enrolled; eight patients had PTSAH (group 1) and 77 did not (group 2). Baseline demographic and clinical characteristics were comparable between the two groups. In group 1, a significantly greater proportion of patients had more than two stent retriever passes (62.5% vs 18.2%, P=0.01), a stent retriever positioned ≥2 cm along an M2 branch (100% vs 30.2%, P=0.002), and the presence of severe iatrogenic vasospasm before SRT pass (37.5% vs 5.2%, P=0.02). One patient with PTSAH and associated mass effect deteriorated clinically. CONCLUSIONS: An increased number of stent retriever passes, distal device positioning, and presence of severe vasospasm were associated with PTSAH. Neurological deterioration with PTSAH can occur.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".