Early Trajectory of Stroke Severity Predicts Long-Term Functional Outcomes in Ischemic Stroke Subjects
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The trajectory of neurological improvement after stroke treatment is clinically likely to be an important prognostic signal. We compared the accuracy of early longitudinal National Institutes of Health Stroke Scale (NIHSS) measurement versus other early markers of stroke severity post treatment in predicting subjects' 90-day stroke outcome. METHODS: Data are from the Endovascular treatment for Small Core and Anterior circulation Proximal occlusion with ESCAPE trial (Endovascular Treatment for Small Core and Anterior Circulation Proximal Occlusion With Emphasis on Minimizing CT to Recanalization Times). Stroke severity was assessed at baseline, 1, 2, 5, 30, and 90 days. Subjects' functional outcome was assessed using the modified Rankin Scale at baseline, 30 days, and 90 days. Group-based trajectory model was used to identify distinct subgroups of longitudinal trajectories of NIHSS measured over the first 2, 5, and 30 days. The accuracy of baseline NIHSS, infarct volume, 24-hour change in NIHSS, infarct volume, and disease severity trajectory subgroups in predicting 90-day stroke outcome were assessed using logistic regression analysis. RESULTS: Group-based trajectory model of the 2-day longitudinal NIHSS data revealed 3 distinct subgroups of NIHSS trajectories-large improvement (41.6%), minimal improvement (31.1%), and no improvement (27.3%) subgroups. Individuals in the large improvement group were more likely were more likely to exhibit good outcomes after 90 days than those in the minimal improvement or no improvement subgroup. Among candidate predictors, the 2-day trajectory subgroup variable was the most accurate in predicting 90-day modified Rankin Scale at 84.5%. CONCLUSIONS: Early trajectory of neurological improvement defined by 2-day longitudinal NIHSS data predicts functional outcomes with greater accuracy than other common variables. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT01778335.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 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".