Petechial hemorrhage in mechanical thrombectomy for distal and medium-vessel occlusions: technical considerations and outcomes
Bibliographic record
Abstract
OBJECTIVE: Mechanical thrombectomy (MT) is well established for large-vessel occlusion (LVO) strokes, but its safety in distal and medium-vessel occlusions (DMVOs) requires further investigation. This study analyzed the relationship between procedural approaches, petechial hemorrhage (PetH), and clinical outcomes in DMVO thrombectomy, with particular attention to technical considerations and the complex interplay between tissue injury and hemorrhagic complications. METHODS: A retrospective cohort study was conducted on DMVO stroke patients treated with MT at 37 stroke centers worldwide from 2016 to 2024. Patients were categorized based on follow-up imaging into those with or without PetH. Four logistic regression models analyzed the association of PetH with favorable functional outcomes (modified Rankin Scale score ≤ 2) at 90 days, early neurological improvement (≥ 4-point National Institutes of Health Stroke Scale score decrease at 24 hours), all-cause mortality, and independent determinants of PetH. Adjusted odds ratios (aORs), 95% confidence intervals, and p values were reported. RESULTS: Of 1428 patients, 439 (30.7%) developed PetH. Factors independently associated with PetH were multiple thrombectomy passes (aOR 1.58, 95% CI 1.21-2.06; p = 0.001), IV thrombolysis (aOR 1.31, 95% CI 1.01-1.69; p = 0.04), and the combined use of a stent retriever with aspiration as the first-line method compared with aspiration alone (aOR 1.66, 95% CI 1.15-2.38; p = 0.007). Conversely, general anesthesia (aOR 0.55, 95% CI 0.40-0.77; p < 0.001), higher Alberta Stroke Program Early CT Scores (aOR 0.76, 95% CI 0.69-0.83; p < 0.001), and successful recanalization (aOR 0.56, 95% CI 0.39-0.80; p = 0.002) were significantly associated with a lower odds of PetH. PetH was associated with a decreased odds of favorable functional outcomes (aOR 0.51, 95% CI 0.36-0.73; p < 0.001), reduced early neurological improvement (aOR 0.59, 95% CI 0.44-0.79; p < 0.001), and increased all-cause mortality (aOR 1.84, 95% CI 1.23-2.76; p < 0.001). CONCLUSIONS: PetH is a frequent sequela following MT in DMVO strokes and is associated with poorer outcomes, likely reflecting underlying ischemic injury rather than direct causation. Procedural factors influence PetH risk, suggesting medical treatment as first-line therapy for DMVOs, with MT reserved for refractory cases using less aggressive approaches.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".