E-229 Mechanical thrombectomy in low alberta stroke program early CT score (ASPECTS) in hyperacute stroke – a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction/Purpose Major randomized controlled trials of mechanical thrombectomy (MT) for acute ischemic stroke (AIS) failed to include patients presenting hyperacutely with low baseline Alberta Stroke Program Early CT Score (ASPECTS 0-5). Patients experiencing hyperacute strokes (last known well ≤6 hours) can potentially benefit the most from MT. We conducted a systematic review and meta-analysis to report presentation severity and radiographic, clinical, and functional outcomes for hyperacute stroke patients presenting with low ASPECTS. Materials and Methods Our comprehensive literature search of PubMed, Embase, and Cochrane databases up to August 31, 2022 included articles reporting patients presenting hyperacutely who underwent MT for AIS with an ASPECTS ≤5 on baseline imaging. Pooled averages were calculated for age and presenting National Institutes of Health Stroke Scale (NIHSS) score. Fixed-effects and random-effects meta-analyses for weighted estimation of overall rates were performed. Forest plots were generated for proportions and estimated overall outcome rates. Results Eighteen studies (1958 patients) were included (mean age=64.1 years; presenting NIHSS score=18.4). Final modified Thrombolysis in Cerebral Infarction 2b-3 grade was achieved in 76.4% (figure 1a), with symptomatic intracranial hemorrhage in 12.1%. Good (modified Rankin Scale [mRS] 0-2 score) (figure 1b) and ambulatory (mRS 0-3 score) 3-month outcomes were achieved by 27.4% and 46.7%, respectively; 90-day mortality was 26.4%. Conclusion MT in hyperacute stroke patients with low ASPECTS (≤5) may result in ambulatory clinical outcomes with acceptable hemorrhage risk. Although a high proportion of patients achieved successful recanalization, this benefit did not fully translate to better clinical outcomes. Disclosures A. Baig: None. M. Bouslama: None. R. Turner: None. A. Aguirre: None. C. Kuo: None. J. Lim: None. B. Donnelly: None. P. Lai: None. K. Raygor: None. E. Levy: 2; C; Claret Medical, GLG Consulting, Guidepoint Global, Imperial Care, Medtronic, Rebound, StimMed, Misionix, Mosiac, and others. 4; C; NeXtGen Biologics, RAPID Medical, Claret Medical, Cognition Medical, Imperative Care, Rebound Therapeutics, StimMed, and others. A. Siddiqui: 2; C; Amnis Therapeutics, Apellis Pharmaceuticals, Inc., Boston Scientific, Canon Medical Systems USA, Inc., Cardinal Health 200, LLC, Cerebrotech Medical Systems, Inc., Cerenovus, and others. 4; C; Adona Medical, Inc., Amnis Therapeutics, Bend IT Technologies, Ltd., BlinkTBI, Inc, Buffalo Technology Partners, Inc., Cardinal Consultants, LLC, Cerebrotech Medical Systems, Inc, and others.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.028 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".