Successful Reperfusion With Mechanical Thrombectomy Is Associated With Reduced Disability and Mortality in Patients With Pretreatment Diffusion-Weighted Imaging–Alberta Stroke Program Early Computed Tomography Score ≤6
Bibliographic record
Abstract
Background and Purpose— In acute ischemic stroke patients, diffusion-weighted imaging (DWI)–Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is correlated with infarct volume and is an independent factor of functional outcome. Patients with pretreatment DWI-ASPECTS ≤6 were excluded or under-represented in the recent randomized mechanical thrombectomy trials. Our aim was to assess the impact of reperfusion in pretreatment DWI-ASPECTS ≤6 patients treated with mechanical thrombectomy. Methods— We analyzed data collected between January 2012 and August 2015 in a bicentric prospective clinical registry of consecutive acute ischemic stroke patients treated with mechanical thrombectomy. Every patient with a documented internal carotid artery or middle cerebral artery occlusion with pretreatment DWI-ASPECTS ≤6 was eligible for this study. The primary end point was a favorable outcome defined by a modified Rankin Scale score ≤2 at 90 days. Results— Two hundred and eighteen patients with a DWI-ASPECTS ≤6 were included. Among them, 145 (66%) patients had successful reperfusion at the end of mechanical thrombectomy. Reperfused patients had an increased rate of favorable outcome (38.7% versus 17.4%; P =0.002) and a decreased rate of mortality at 3 months (22.5% versus 39.1%; P =0.013) compared with nonreperfused patients. The symptomatic intracranial hemorrhage rate was not different between the 2 groups (13.0% versus 14.1%; P =0.83). However, in patients with DWI-ASPECTS <5, favorable outcome was low (13.0% versus 9.5%; P =0.68) with a high mortality rate (45.7% versus 57.1%; P =0.38) with or without successful reperfusion. Conclusions— Successful reperfusion is associated with reduced mortality and disability in patients with a pretreatment DWI-ASPECTS ≤6. Further data from randomized studies are needed, particularly in patients with DWI-ASPECTS <5.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".