Endovascular reperfusion outcomes in patients with a stroke and low ASPECTS is highly dependent on baseline infarct volumes
Bibliographic record
Abstract
BACKGROUND: Patients with large vessel occlusion stroke (LVOS) and a low Alberta Stroke Program Early CT Score (ASPECTS) are often not offered endovascular therapy (ET) as they are thought to have a poor prognosis. OBJECTIVE: To compare the outcomes of patients with low and high ASPECTS undergoing ET based on baseline infarct volumes. METHODS: Review of a prospectively collected endovascular database at a tertiary care center between September 2010 and March 2020. All patients with anterior circulation LVOS and interpretable baseline CT perfusion (CTP) were included. Subjects were divided into groups with low ASPECTS (0-5) and high ASPECTS (6-10) and subsequently into limited and large CTP-core volumes (cerebral blood flow 30% >70 cc). The primary outcome measure was the difference in rates of 90-day good outcome as defined by a modified Rankin Scale (mRS) score of 0 to 2 across groups. RESULTS: 1248 patients fit the inclusion criteria. 125 patients had low ASPECTS, of whom 16 (12.8%) had a large core (LC), whereas 1123 patients presented with high ASPECTS, including 29 (2.6%) patients with a LC. In the category with a low ASPECTS, there was a trend towards lower rates of functional independence (90-day modified Rankin Scale (mRS) score 0-2) in the LC group (18.8% vs 38.9%, p=0.12), which became significant after adjusting for potential confounders in multivariable analysis (aOR=0.12, 95% CI 0.016 to 0.912, p=0.04). Likewise, LC was associated with significantly lower rates of functional independence (31% vs 51.9%, p=0.03; aOR=0.293, 95% CI 0.095 to 0.909, p=0.04) among patients with high ASPECTS. CONCLUSIONS: Outcomes may vary significantly in the same ASPECTS category depending on infarct volume. Patients with ASPECTS ≤5 but baseline infarct volumes ≤70 cc may achieve independence in nearly 40% of the cases and thus should not be excluded from treatment.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".