Abstract 129: Older Age and Shorter Time from Symptom Onset Positively Impacts Outcomes in Moderate Severity Stroke Patients in SENTIS Trial
Bibliographic record
Abstract
Background: A number of recent acute ischemic stroke trials have shown that patients with moderate severity strokes respond most positively to interventional treatments. Similarly, the SENTIS Trial showed that patients with moderate severity stroke had significantly better outcome when treated with NeuroFlo. The current report is a post hoc analysis of patients with moderate stroke in the SENTIS Trial. Methods: SENTIS was a prospective randomized trial of the safety and efficacy of NeuroFlo treatment. A total of 515 patients were enrolled at 68 centers in 9 countries. Modified Rankin Scale (mRS) scores at 90 days were dichotomized into 0-2 versus 3-6 for patients with baseline National Institute of Health Stroke Scale (NIHSS) scores of 8 to 14, and compared between the treated and non-treated groups. Additionally, we evaluated the impact of age, time from symptom onset (TFSO) to randomization, and occlusion location on outcomes in this patient cohort. Results: Of the 515 patients enrolled in SENTIS, 219 patients (42%) with NIHSS 8 to 14 were available for analysis. The table below lists the odds ratio (OR) with 95% confidence intervals (CI) and p-values for the cohorts evaluated. Conclusion: Patients with moderate stroke severity had significantly better outcomes in the treated group compared to the non-treated group in this post hoc analysis of over 40% of patients enrolled in the SENTIS Trial. Additionally, patients 70 years and older and those with TFSO ≤5 hours had significantly better outcomes. To ensure the best efficacy analysis of new ischemic stroke treatments, future studies may focus on patients with moderate severity strokes.
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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 | 0.002 |
| 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) | 0.006 | 0.001 |
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".