Transcranial Doppler ultrasound to evaluate the risk of hyperperfusion after endovascular stroke thrombectomy
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Hemorrhagic transformation (HT) has been reported in up to 50% of acute ischemic stroke (AIS) patients with a large vessel occlusion (LVO) treated with endovascular thrombectomy (EVT). HT may be driven by postrecanalization hyperperfusion injury and is independently associated with worse functional outcomes. Strategies to identify patients at risk for HT may assist in developing preventive therapies. METHODS: We prospectively included adult AIS patients with an anterior circulation LVO achieving successful recanalization after EVT. Consenting participants received transcranial Doppler ultrasound (TCD) within 18 hours of procedure completion. We compared flow velocities according to the presence of HT on the computed tomography scan performed within the first 24±12 hours from the end of EVT. We also evaluated the association of flow velocities with systemic blood pressure (BP) readings at the time of insonation. RESULTS: A total of 48 patients consented to participate in the study. Six (12%) were excluded due to the absence of temporal windows. HT was detected in 20 participants (48%). Those with HT had higher peak systolic velocities on the middle cerebral arteries compared to those without HT for both the symptomatic (107±42 vs. 82±25 cm/second, p = .024) and asymptomatic (97±21 vs. 81±25 cm/second, p = .040) sides. No correlation of flow velocities on either the symptomatic or asymptomatic side and BP measurements at the time of insonation was detected. CONCLUSION: TCD can identify patients at risk of HT following successful EVT. TCD could serve as an inexpensive ancillary test to guide participant selection for clinical trials targeting postprocedural reperfusion injury.
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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 | 0.001 | 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".