Efficacy of endovascular treatment for acute ischemic stroke with large core infarction and its influencing factors
Bibliographic record
Abstract
Objective To investigate the efficacy and influencing factors of early endovascular treatment (EVT) in the patients encountering acute ischemic stroke with large vessel occlusion (AIS-LVO) in the anterior circulation accompanying large core infarction. Methods The clinical data of 31 patients diagnosed as AIS-LVO accompanying large core infarction who underwent EVT in our hospital from January to November 2020 were collected and retrospectively analyzed. Basic information such as age and gender, as well as National Institutes of Health Stroke Scale (NIHSS) score, Alberta Stroke Project Early Computed Tomography (ASPECTS) score, and collateral circulation scores were collected. Postoperative revascularization condition and antiplatelet medication therapy were also recorded. The patients were subsequently divided into good and poor prognosis groups according to the modified Rankin scale (mRS) in 90 d after surgery. The related predictors for good prognosis here explored by multivariate logistic regression analysis. Results Twenty-five cases (80.6%) obtained postoperative revascularization; the incidence of intracranial hemorrhage (ICH) was 41.9%, with 12.9% being symptomatic intracranial hemorrhage (sICH); the good prognosis rate was 32.2% at 90th day after surgery, and the mortality rate was 12.9%. The patients in the good prognosis group had younger age than those in the poor prognosis group (mRS>2) (OR=0.804, 95% CI=0.657~0.983, P=0.034). Conclusion The patients of AIS-LVO accompanying large core infarction can partially benefit from endovascular treatment, and the age of patients is an important factor affecting prognosis.
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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 | 0.007 |
| 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 | 0.000 | 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".