Impact of Age and Baseline NIHSS Scores on Clinical Outcomes in the Mechanical Thrombectomy Using Solitaire FR in Acute Ischemic Stroke Study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Age and stroke severity are inversely correlated with the odds of favorable outcome after ischemic stroke. A previously proposed score for Stroke Prognostication Using Age and NIHSS Stroke Scale (SPAN) indicated that SPAN-100-positive patients (ie, age + NIHSS score = 100 or more) do not benefit from IV-tPA. If this finding holds true for endovascular therapy, this score can impact patient selection for such interventions. This study investigated whether a score combining age and NIHSS score can improve patients' selection for endovascular stroke therapy. MATERIALS AND METHODS: The SPAN index was calculated for patients in the prospective Solitaire FR Thrombectomy for Acute Revascularization study: an international single-arm multicenter cohort for anterior circulation stroke treatment by using the Solitaire FR. The proportion with favorable outcome (90-day mRS score ≤2) was compared between SPAN-100-positive versus-negative patients. RESULTS: Of the 202 patients enrolled, 196 had baseline NIHSS scores. Fifteen (7.7%) patients were SPAN-100-positive. There was no difference in the rate of successful reperfusion (Thrombolysis In Cerebral Infarction 2b or 3) between SPAN-100-positive versus -negative groups (93.3% versus 82.8%, respectively; P = .3). Stroke SPAN-100-positive patients had a significantly lower proportion of favorable clinical outcomes (26.7% versus 60.8% in SPAN-100-negative, P = .01). In a multivariable analysis, SPAN-100-positive status was associated with lower odds of favorable outcome (OR, 0.3; 95% CI, 0.1-0.9; P = .04). A higher baseline Alberta Stroke Program Early CT Score and a short onset to revascularization time also predicted favorable outcome in the multivariable analysis. CONCLUSIONS: A significantly lower proportion of patients with a positive SPAN-100 achieved favorable outcome in this cohort. SPAN-100 was an independent predictor of favorable outcome after adjusting for time to treatment and the extent of preintervention tissue damage according to the Alberta Stroke Program Early CT Score.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".