Identifying the predictors of ultra early neurological improvement and its role in functional outcome after endovascular thrombectomy in acute ischemic stroke
Bibliographic record
Abstract
Background and purpose Using post-treatment methods to predict functional outcomes of acute ischemic stroke (AIS) patients undergoing endovascular thrombectomy (EVT) is crucial in stroke medicine. The National Institute of Health Stroke Scale (NIHSS) score at 24 h has been widely used; however, there is a paucity of data on using earlier NIHSS scores and their association with outcome. In this study, we aimed to investigate the usage of NIHSS at 1-h time window -ultra-early neurological improvement (UENI)- as a surrogate marker associated with the functional outcomes of AIS patients treated with EVT. Methods We included 485 adults (≥18 years old) who underwent emergency EVT at four academic comprehensive stroke centers between 2020 and 2021. Patients with pre-EVT Alberta Stroke Program Early CT Score (ASPECTS) < 6, missing follow-up data, and missing data of the first hour NIHSS were excluded (n = 20). UENI was defined as post-EVT NIHSS reduction of 4 points or more or NIHSS as 0–1 within 1-h post-EVT. An mRS score of 0–2 after three months was defined as favorable outcome, and independent walking independence was defined as mRS of 3. Results A total of 465 patients were included in our final analysis. We identified 122 (26.2%) patients with UENI. While 82.79% of the patients with UENI achieved favorable functional outcomes at 3-months, only 32.36% of patients without UENI had favorable functional outcome (p < 0.0001). In addition, lower hospitalization costs were associated with patients who had UENI, compared to No-UENI (p = 0.003). A multivariate logistic regression analysis revealed that younger age (p < 0.0001), shorter last know normal to puncture time (LKNPT) (p = 0.013), higher pre-treatment ASPECTS (p = 0.039), final modified thrombolysis in cerebral infarction (mTICI) ≥2b (p = 0.002), and fewer number of EVT attempts (p = 0.002) were variables independently associated with UENI. The presence of UENI was independently associated with a better outcome OR: 7.999 (95% C.I. 4.415–14.495). Conclusion UENI was observed in about a quarter of patients with AIS undergoing EVT. Younger age, shorter LKNPT, higher pre-treatment ASPECTS, final mTICI≥2b, and fewer number of EVT attempts, were independently associated with UENI. The presence of UENI was independently associated with better functional outcome at 3 months.
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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) | 0.001 | 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".