Tissue Clock Beyond Time Clock: Endovascular Thrombectomy for Patients With Large Vessel Occlusion Stroke Beyond 24 Hours
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Randomized trials proved the benefits of mechanical thrombectomy (MT) for select patients with large vessel occlusion (LVO) within 24 hours of last-known-well (LKW). Recent data suggest that LVO patients may benefit from MT beyond 24 hours. This study reports the safety and outcomes of MT beyond 24 hours of LKW compared to standard medical therapy (SMT). METHODS: This is a retrospective analysis of LVO patients presented to 11 comprehensive stroke centers in the United States beyond 24 hours from LKW between January 2015 and December 2021. We assessed 90-day outcomes using the modified Rankin Scale (mRS). RESULTS: Of 334 patients presented with LVO beyond 24 hours, 64% received MT and 36% received SMT only. Patients who received MT were older (67±15 vs. 64±15 years, P=0.047) and had a higher baseline National Institutes of Health Stroke Scale (NIHSS; 16±7 vs.10±9, P<0.001). Successful recanalization (modified thrombolysis in cerebral infarction score 2b-3) was achieved in 83%, and 5.6% had symptomatic intracranial hemorrhage compared to 2.5% in the SMT group (P=0.19). MT was associated with mRS 0-2 at 90 days (adjusted odds ratio [aOR] 5.73, P=0.026), less mortality (34% vs. 63%, P<0.001), and better discharge NIHSS (P<0.001) compared to SMT in patients with baseline NIHSS ≥6. This treatment benefit remained after matching both groups. Age (aOR 0.94, P<0.001), baseline NIHSS (aOR 0.91, P=0.017), Alberta Stroke Program Early Computed Tomography (ASPECTS) score ≥8 (aOR 3.06, P=0.041), and collaterals scores (aOR 1.41, P=0.027) were associated with 90-day functional independence. CONCLUSION: In patients with salvageable brain tissue, MT for LVO beyond 24 hours appears to improve outcomes compared to SMT, especially in patients with severe strokes. Patients' age, ASPECTS, collaterals, and baseline NIHSS score should be considered before discounting MT merely based on LKW.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".