Value of 24- to 48-Hour Infarct Volume as a Surrogate for Clinical Outcome in Late-Window Thrombectomy May Be Limited: A Post Hoc Analysis of the AURORA Collaboration
Bibliographic record
Abstract
BACKGROUND: The utility of 24- to 48-hour follow-up infarct volume (FIV) as a surrogate outcome in late time-window acute ischemic stroke is unclear. We aimed to determine associations of 24- to 48-hour FIV and clinical outcome in patients presenting >6 hours from last known well with and without endovascular treatment (EVT). METHODS: Post hoc analysis of the AURORA (Thrombectomy for Anterior Circulation Stroke Beyond 6 h From Time Last Known Well) patient-level meta-analysis of 6 randomized trials of late-window EVT. Patients were randomized to EVT or the control arm (best medical care). FIV was assessed on follow-up computed tomography or magnetic resonance imaging at 24 to 48 hours. Multivariable binary logistic regression with adjustment for key covariates was performed to estimate probabilities of achieving functional independence (modified Rankin Scale [mRS] score, 0-2 at 90 days) based on FIV. Mediation analysis was performed to determine the proportion of the EVT effect that is explained by FIV reduction. RESULTS: <0.01). In the EVT arm, the estimated probability of achieving an mRS score of 0 to 2 declined with increasing FIV, from 65% at 0 mL FIV to 4% at 200 mL. In the control arm, this association was weaker, and the mRS score of 0 to 2 probabilities were overall lower. Only 5.9% of EVT's effect on clinical outcome was explained by FIV reduction. CONCLUSIONS: FIV mediated only a small proportion of the EVT effect on clinical outcome, and the association of FIV and outcomes was much weaker; overall outcomes were worse in the control arm compared with the EVT arm. For FIV up to 100 mL, EVT results in substantially better clinical outcomes than best medical management given the same FIV. The utility of FIV as a surrogate outcome in late time-window stroke may be limited.
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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 | 0.039 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.034 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".