Abstract WP27: Alteration in Clinical Outcome Between Discharge and Three Months After Mechanical Thrombectomy versus Medical Management in Late-Presenting Stroke Patients
Bibliographic record
Abstract
Background: Mechanical thrombectomy in late-presenting stroke patients with a limited infarct core on CTP/DWI is highly effective. We aimed to evaluate the degree of disability at discharge as an indicator for functional impairment at one and three months after mechanical thrombectomy compared to medical management in these patients. Methods: This study concerns a post-hoc analysis of the DAWN-trial population. Patients presenting 6-24h after symptom onset of an emergent large vessel occlusion with mismatch between symptom severity and infarct size on CTP/DWI, were randomized for medical management versus mechanical thrombectomy. We assessed the change in modified Rankin score (mRS) from discharge up to three months post-stroke for DAWN-patients treated with mechanical thrombectomy compared to those randomized to medical management. Kendall’s tau test was used to evaluate the correlation between the mRS at discharge, at 30 days, and at 90 days. Mixed models were used to explore the potential difference between treatment arms in the change of utility weighted mRS over time. Results: Ninety-eight of 107 patients treated with mechanical thrombectomy and 89/99 controls survived at discharge and were included in the analysis. We found a strong correlation between the mRS at discharge, at 30 days, and at 90 days for both treatment arms with a tau varying from 0.52 to 0.72 for mechanical thrombectomy and 0.56 to 0.71 for medical management. All correlation coefficients were statistically significant (p < 0.0001). The utility weighted mRS after mechanical thrombectomy was consistently superior to medical management (p < 0.0001). Although there was a trend towards a stronger dispersion of the utility weighted mRS over time after mechanical thrombectomy, there was no statistically significant interaction effect between time and treatment arm (p 0.44). Conclusion: The treatment effect of mechanical thrombectomy occurs early and further improvement over time is similar to that of medical management. The mRS at discharge is a robust indicator for functional status at one and three months post stroke and may therefore be used as an alternative measure for clinical outcome.
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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) | 0.001 | 0.001 |
| 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) | 0.002 | 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".