Futile recanalization after endovascular treatment in acute ischemic stroke with large ischemic core
Bibliographic record
Abstract
BACKGROUND: Endovascular therapy (EVT) is the treatment of choice for acute ischemic stroke (AIS) with large vessel occlusion. However, in many patients, successful EVT recanalization does not correspond to a clinical improvement, called futile recanalization (FR). We aimed to identify stroke risk factors and patient characteristics associated with FR in AIS with large core infarct (LCI). METHODS: A total of 137 patients with AIS with LCI treated by EVT at a single stroke center were retrospectively included from January 2016 to June 2023. LCI was defined by Diffusion-Weighted Imaging-Alberta Stroke Program Early Computed Tomography Score (DWI-ASPECT) < 6. Patient age, sex, modified Rankin Scale (mRS), National Institutes of Health Stroke Scale (NIHSS), time to treatment, risk factors, and radiologic findings were collected, and potential associations with FR were analyzed. FR was defined as successful reperfusion with modified Thrombolysis in Cerebral Infarction (mTICI) ≥ 2b but without functional independence at 90 days (mRS ≥ 3). A multivariate logistic regression analysis was conducted on the clinical characteristics of patients, based on the presence or absence of FR, and the factors influencing FR. RESULTS: Of 137 patients, 120 showed successful recanalization (mTICI ≥ 2b). All patients were divided into FR (n = 80) and no FR (n = 40) groups. Older age (odds ratio [OR] 1.052, 95% confidence interval [CI] 1.002-1.105; p = 0.041), the higher the initial NIHSS score (OR 1.181, 95% CI 1.037-1.344; p = 0.012), and prior intravenous plasminogen activator (OR 0.310, 95% CI 0.118-0.813, p = 0.017) were independent influencing factors of FR. CONCLUSIONS: The older age, the higher the initial NIHSS, and not receiving intravenous plasminogen activator were independently associated with FR in AIS with LCI. These factors could identify poor responders to EVT recanalization.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".