Abstract TMP96: Clear Thrombectomy Score: An Index to Estimate Probability of Good Functional Outcome Following Endovascular Treatment in the Late Window for Anterior Circulation Occlusion
Bibliographic record
Abstract
Background: Endovascular thrombectomy (EVT) has established efficacy across a wide range of patient age, radiological findings, and clinical features. However, EVT may be less effective in extreme scenarios (e.g., large established infarction in later treatment windows), where there are currently limited data. Methods: A heterogeneous, multinational observational cohort (CLEAR registry) of consecutive adult patients ≥18 years old who underwent EVT for acute occlusion (2014-2022) of the internal carotid or proximal middle cerebral (M1 or M2) arteries was queried (n=64 sites). A high-fidelity model for predicting good functional outcome at 90 days (return to pre-stroke modified Rankin Scale [mRS] or mRS 0-2 after EVT) was developed using a binary, multivariable logit model with adaptive double lasso adjustment, which was validated using 5-fold cross validation and 1000 bootstrap sampling for confidence intervals. Results: At the time of the analysis, we evaluated 2953 patients from the registry treated with EVT, of which 1855 (63%) had complete covariate data for inclusion. The median National Institutes of Health Stroke Scale (NIHSS) score was 15 (IQR 9-20), with 14.0% having a pre-stroke mRS >2, 8.3% having a NIHSS <6, and 17.8% having an Alberta Stroke Program Early Computed Tomography Scale (ASPECTS) score ≤6. A good functional outcome occurred in 813 (43.8%) patients. Independent predictors of the primary outcome, with points allocated toward the final score, included younger age, higher ASPECTS, lower NIHSS, and time from last known well to arterial puncture. The areas under the curve for derivation and validation cohorts were 0.72 (95% CI 0.70-0.75) and 0.74 (95% CI 0.71-0.80), respectively. Discussion: The CLEAR thrombectomy score provides a simple, validated means of predicting good functional outcome following late-window, anterior circulation thrombectomy using routinely acquired clinical and imaging data. External validation is warranted.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".