Mechanical Thrombectomy in Anterior Circulation Occlusion Could Be More Effective than Medical Management Even in Low DWI-ASPECTS Patients
Bibliographic record
Abstract
The purpose of this study was to investigate whether patients with low preoperative Diffusion-weighted Imaging Alberta Stroke Program Early Computed Tomography Score (DWI-ASPECTS) could benefit from mechanical thrombectomy for acute anterior circulation occlusion. This was a retrospective, non-blinded, cohort study. From September 2012 to August 2016, 83 consecutive patients of acute anterior circulation occlusion were treated with thrombectomy using second-generation devices or medical management. The DWI-ASPECTS was scored after the first MRI. Patient characteristics and clinical outcomes were compared between the treatment groups. Significant dependence was defined as a modified Rankin scale score ≥3 at 90 days. As a result, 33 patients underwent mechanical thrombectomy and 50 received medical management. In the mechanical thrombectomy group, the variable of lower DWI-ASPECTS (5, 4-6 vs. 8, 7-8, P < 0.001), especially ≤6, was significantly associated with poor prognosis. However, compared with patients of DWI-ASPECTS ≤ 6 who received medical management, there were significantly fewer patients with poor outcomes in thrombectomy (dependent in 11 of 15 vs. 23 of 23, respectively; P = 0.019). Although patients with lower pretreatment DWI-ASPECTS could benefit less from thrombectomy, their outcomes were still better than medical management. Therefore, mechanical thrombectomy could be considered in some patients with low pretreatment DWI-ASPECTS.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".