Cerebral Edema in Patients With Large Hemispheric Infarct Undergoing Reperfusion Treatment: A HERMES Meta-Analysis
Bibliographic record
Abstract
Background and Purpose: Whether reperfusion into infarcted tissue exacerbates cerebral edema has treatment implications in patients presenting with extensive irreversible injury. We investigated the effects of endovascular thrombectomy and reperfusion on cerebral edema in patients presenting with radiological evidence of large hemispheric infarction at baseline. Methods: In a systematic review and individual patient-level meta-analysis of 7 randomized controlled trials comparing thrombectomy versus medical therapy in anterior circulation ischemic stroke published between January 1, 2010, and May 31, 2017 (Highly Effective Reperfusion Using Multiple Endovascular Devices collaboration), we analyzed the association between thrombectomy and reperfusion with maximal midline shift (MLS) on follow-up imaging as a measure of the space-occupying effect of cerebral edema in patients with large hemispheric infarction on pretreatment imaging, defined as diffusion-magnetic resonance imaging or computed tomography (CT)-perfusion ischemic core 80 to 300 mL or noncontrast CT-Alberta Stroke Program Early CT Score ≤5. Risk of bias was assessed using the Cochrane tool. Results: Among 1764 patients, 177 presented with large hemispheric infarction. Thrombectomy and reperfusion were associated with functional improvement (thrombectomy common odds ratio =2.30 [95% CI, 1.32–4.00]; reperfusion common odds ratio =4.73 [95% CI, 1.66–13.52]) but not MLS (thrombectomy β=−0.27 [95% CI, −1.52 to 0.98]; reperfusion β=−0.78 [95% CI, −3.07 to 1.50]) when adjusting for age, National Institutes of Health Stroke Score, glucose, and time-to-follow-up imaging. In an exploratory analysis of patients presenting with core volume >130 mL or CT-Alberta Stroke Program Early CT Score ≤3 (n=76), thrombectomy was associated with greater MLS after adjusting for age and National Institutes of Health Stroke Score (β=2.76 [95% CI, 0.33–5.20]) but not functional improvement (odds ratio, 1.71 [95% CI, 0.24–12.08]). Conclusions: In patients presenting with large hemispheric infarction, thrombectomy and reperfusion were not associated with MLS, except in the subgroup with very large core volume (>130 mL) in whom thrombectomy was associated with increased MLS due to space-occupying ischemic edema. Mitigating cerebral edema-mediated secondary injury in patients with very large infarcts may further improve outcomes after reperfusion therapies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.003 | 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 teacher head, 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".