Analysis of factors influencing short-term outcomes after early interventional therapy for acute ischaemic stroke
Bibliographic record
Abstract
OBJECTIVE: This study aimed to investigate the potential factors influencing the early efficacy outcomes of patients with acute ischaemic stroke (AIS) after endovascular interventional therapy. METHODS: A retrospective analysis was conducted involving 326 patients with AIS. The early efficacy outcomes and complications among patients after emergency cerebrovascular intervention were evaluated. Univariate analysis was performed to compare the baseline data between good outcome and poor outcome groups. Binary logistic regression analysis was used to determine the independent risk factors for poor outcomes at discharge. RESULTS: Among the 326 patients, 174 (53.4%) had poor outcomes at discharge. Univariate analysis showed that a poor prognosis was associated with age, history of atrial fibrillation and stroke, a high preoperative National Institutes of Health Stroke Scale (NIHSS) score, a low thrombolysis in cerebral infarction (TICI) grade after thrombectomy, and a high incidence of postoperative symptomatic intracranial haemorrhage and cerebral oedema/hernia (P < 0.05). Binary logistic regression analysis showed that age (P = 0.010), NIHSS score before surgery (P < 0.001), the Alberta Stroke Program Early CT Score (ASPECTS) before surgery (P < 0.001), TICI grade after thrombectomy (P < 0.001), symptomatic intracranial haemorrhage after surgery (P = 0.001) and cerebral oedema/hernia after surgery (P = 0.004) were independent risk factors for a poor outcome at discharge. CONCLUSION: Age, NIHSS score before surgery, ASPECTS before surgery, TICI grade after thrombectomy, symptomatic intracranial haemorrhage, and cerebral oedema/hernia after surgery were independent risk factors for poor short-term outcomes after endovascular interventional therapy for AIS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".