Recanalization Does Not Always Equate to Reperfusion: No-Reflow Phenomenon After Successful Thrombectomy
Bibliographic record
Abstract
BACKGROUND: Thrombectomy for acute large vessel occlusion is a well-established treatment for stroke prevention. However, futile recanalization cases, where no-reflow occurs despite successful recanalization, have been reported. This study aimed to assess cerebral hemodynamics immediately after thrombectomy and their relationship with clinical outcomes. METHODS: We prospectively enrolled patients who underwent successful thrombectomy (modified Thrombolysis in Cerebral Infarction [TICI] ≥2b) for internal carotid artery or middle cerebral artery occlusions at Nagasaki University Hospital between January 2021 and December 2023. Preoperative magnetic resonance imaging was performed, followed by flat-panel computed tomography perfusion 30 minutes after recanalization. Areas with cerebral blood flow <45%, Tmax >6 seconds, and cerebral blood volume <34%, 38%, and 42% were analyzed, and hypoperfusion intensity ratio and cerebral blood volume index were calculated using Rapid ANGIO. We assessed the correlation of these parameters with infarct expansion, hemorrhagic transformation, and poor outcomes, defined as modified Rankin Scale scores of 4 to 6, at 3 months. RESULTS: =0.039). CONCLUSIONS: No-reflow is common after thrombectomy, suggesting that successful recanalization does not always result in immediate tissue reperfusion. Hemodynamic impairment postthrombectomy may persist, highlighting the need for adjunctive treatments.
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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 | 0.003 |
| 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 | 0.000 |
| 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".