Baseline ASPECTS predicts early neurological deterioration and functional outcomes after endovascular thrombectomy in acute ischemic stroke
Bibliographic record
Abstract
Background Early neurological deterioration (END), defined as neurological decline after endovascular thrombectomy (EVT) for acute ischemic stroke (AIS), is a critical complication associated with poor long-term prognosis. Although END significantly impacts clinical outcomes, its underlying mechanisms and modifiable risk factors remain poorly understood. This study aimed to (1) characterize the clinical profile of END and (2) evaluate its association with 90-day functional outcomes in AIS patients who underwent EVT. Methods This retrospective study included consecutive patients with acute ischemic stroke (AIS) secondary to large vessel occlusion (LVO) who were treated with endovascular thrombectomy (EVT) between January 2021 and December 2024. END was defined as either a ≥4-point increase in the National Institutes of Health Stroke Scale (NIHSS) score or a ≥1-point increase in the NIHSS consciousness subscore (Item Ia) within 72 h after EVT. Patients meeting these criteria were classified into the END group; others comprised the non-END group. Variables with a p -value of <0.05 in univariate analysis were included in a multivariable logistic regression model to identify independent predictors of END. The predictive performance of the Alberta Stroke Program Early CT Score (ASPECTS) was assessed through receiver operating characteristic (ROC) analysis, with the optimal cutoff determined by maximizing the Youden index. Results The study included 177 consecutive AIS patients with LVO who were treated with EVT. END occurred in 52 patients (29.4%). The END group had significantly lower baseline ASPECTS values than the non-END group (median [IQR]: 7 [6–8] vs. 9 [8–9], p < 0.001). In the adjusted analysis, higher ASPECTS was independently associated with a reduced risk of END (OR = 0.59 per 1-point increase, 95% CI: 0.44–0.80, p = 0.001). ROC analysis identified an ASPECTS ≤7 as the optimal cutoff for predicting END (AUC = 0.761; sensitivity 75.0%, specificity 76.8%). At 90 days, functional independence [modified Rankin Scale (mRS) 0–2] was achieved in 52.0% of the non-END group versus 7.6% of the END group ( p < 0.001). Conclusion END after EVT independently predicts poor 90-day functional independence (mRS 0–2) in LVO-related AIS. Our findings support incorporating a baseline ASPECTS ≤7 into risk stratification protocols to identify high-risk patients requiring intensive neuromonitoring (hourly NIHSS assessments for 72 h post-EVT). Early detection of END signs, such as a ≥ 4-point increase in the NIHSS score 4, may enable prompt interventions (e.g., blood pressure control or edema management) to improve long-term outcomes.
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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 | 0.000 |
| 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) | 0.001 | 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".