Duration of Ischemia Affects Outcomes Independent of Infarct Size in Stroke
Bibliographic record
Abstract
BACKGROUND: Delays in endovascular reperfusion for patients with large vessel occlusion stroke are known to worsen outcomes, and the mechanism is believed to be time-dependent expansion of the ischemic infarction. In this study, we hypothesize that delays in onset to reperfusion (OTR) assert an effect on outcomes independent of effects of final infarct (FI). METHODS: We performed a subgroup analysis from the prospective multicenter COMPLETE (International Acute Ischemic Stroke Registry With the Penumbra System Aspiration Including the 3D Revascularization Device; Penumbra, Inc) registry for 257 patients with anterior circulation large vessel occlusion who underwent endovascular therapy with successful reperfusion (modified treatment in cerebral infarction score 2b/3). FI was measured by Alberta Stroke Program Early CT score and volume on 24- to 48-hour computed tomography or magnetic resonance imaging. The likelihood of 90-day good functional outcome (modified Rankin scale 0-2) was assessed by OTR and absolute risk difference (ARD) was estimated using multivariable logistic regressions adjusting for patient characteristics including FI. RESULTS: In univariable analysis, longer OTR was associated with a decreased likelihood of good functional outcome (ARD -3% [95% CI -4.5 to -1.0]/h delay). In multivariable analysis accounting for FI, the association between OTR and functional outcome remained significant (ARD -2% [95% CI -3.5 to -0.4]/h delay) with similar ARD. This finding was maintained in the subset of patients with FI imaging using CT only, using Alberta Stroke Program Early CT Score or volumetric FI measurements, and also in patients with larger versus smaller FIs. CONCLUSIONS: The impact of OTR on outcomes appears to be mostly through a mechanism that is independent of FI. Our findings suggest that although the field has moved toward imaging infarct core definitions of eligibility for endovascular treatment, time remains an important predictor of outcome, independent of infarct core.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".