Endovascular therapy for large ischemic stroke in directly admitted versus transferred patients: A secondary analysis
Bibliographic record
Abstract
Background: Endovascular therapy (EVT) has been proved beneficial in patients with acute large vessel occlusion (LVO) with large infarcts, but it is unknown whether the benefit would be affected by the interhospital-transfer status. We investigated the efficacy of EVT according to the interhospital-transfer status in such patients. Methods: This was a secondary analysis of the ANGEL-ASPECT trial. Patients with acute anterior-circulation LVO and large infarcts, defined by Alberta stroke program early CT score (ASPECTS) 3–5 or infarct core volume 70–100 mL, were enrolled from 46 centers across China and randomized (1:1) to receive EVT with medical management (MM) versus MM alone. We dichotomized patients into two subgroups based on whether admitted directly to the EVT-capable center or transferred from a primary center. The primary outcome was the 90-day modified Rankin Scale (mRS). Results: From October 2020 to May 2022, 456 patients were recruited and one withdrew consent. So, 455 patients were included in this analysis, with 210 (46.2%) in the direct subgroup and 245 (53.8%) in the transfer subgroup. The transfer subgroup had longer median onset-to-arrival time than the direct patients (379 vs 279 mins, p < 0.001), while there was no significant difference in the arrival-to-recanalization time (197 vs 205 mins, p = 0.087) between the two subgroups. A significant ordinal shift of 90-day mRS toward a better functional outcome in EVT than MM (generalized odds ratio [gOR] = 1.67; 95% confidence interval (CI) = 1.03–2.70, p = 0.036 versus gOR = 1.60; 95% CI = 1.02–2.50, p = 0.039) was found in the direct and transfer group, respectively. There was no significant interaction of the two subgroups over the treatment effect of EVT versus MM on the primary outcome ( p for interaction = 0.706). Conclusions: In acute anterior-circulation LVO patients with large infarcts, the benefit of EVT compared to MM did not vary by the interhospital-transfer status.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".