Endovascular Therapy in Strokes with ASPECTS 5-7 May Result in Smaller Infarcts and Better Outcomes as Compared to Medical Treatment Alone
Bibliographic record
Abstract
INTRODUCTION: Intra-arterial therapy (IAT) for large vessel occlusion strokes (LVOS) has been increasingly utilized. The benefit of IAT in patients with midrange Alberta Stroke Program Early Computed Tomography Score (ASPECTS) remains to be established. MATERIALS AND METHODS: This was a retrospective analysis of LVOS with ASPECTS 5-7 treated with IAT (n = 86) or medical therapy alone (intravenous tissue plasminogen activator; n = 15) at two centers from 2009 to 2012. Definitions were as follows: symptomatic intracranial hemorrhage = any parenchymal hematoma; successful reperfusion = mTICI ≥2b; good and acceptable outcomes = 90-day mRS 0-2 and 0-3, respectively. Final infarct volumes (FIV) were calculated based on 24-hour CT/MRI scans. RESULTS: Mean age (67 ± 14 vs. 67 ± 19 years) and baseline NIHSS (20 ± 5 vs. 20 ± 6) were similar in the two groups. Successful reperfusion was achieved in 58 (67%) IAT patients. Symptomatic and asymptomatic intracranial hemorrhage occurred in 9 (10%) and 31 (36%) IAT patients, respectively. The proportion of 90-day good and acceptable outcomes was 20 (17/86) and 33% (28/86), respectively. Successful IAT reperfusion was associated with smaller FIV (p = 0.015) and higher rates of good (p = 0.01) and acceptable (p = 0.014) outcomes. There was a strong trend towards a higher hemicraniectomy requirement in medically as compared to endovascularly treated patients (20 vs. 6%; p = 0.06) despite similar in-hospital mortality. The median FIV was significantly lower with IAT versus medical therapy [80 ml (interquartile range, 38-122) vs. 190 ml (121-267); p = 0.015]. CONCLUSIONS: Despite a relatively low probability of achieving functional independence, IAT in LVOS patients with ASPECTS 5-7 appears to result in lower degrees of disability and may lessen the need for hemicraniectomy. Therefore, it may be a reasonable option for patients and families who favor a shift from severe to moderate disability.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".