Clinical outcome of patients with mild pre-stroke morbidity following endovascular treatment: a HERMES substudy
Bibliographic record
Abstract
BACKGROUND: Analyses of the effect of pre-stroke functional levels on the outcome of endovascular therapy (EVT) have focused on the course of patients with moderate to substantial pre-stroke disability. The effect of complete freedom from pre-existing disability (modified Rankin Scale (mRS) 0) versus predominantly mild pre-existing disability/symptoms (mRS 1-2) has not been well delineated. METHODS: The HERMES meta-analysis pooled data from seven randomized trials that tested the efficacy of EVT. We tested for a multiplicative interaction effect of pre-stroke mRS on the relationship between treatment and outcomes. Ordinal regression was used to assess the association between EVT and 90-day mRS (primary outcome) in the subgroup of patients with pre-stroke mRS 1-2. Multivariable regression modeling was then used to test the effect of mild pre-stroke disability/symptoms on the primary and secondary outcomes (delta-mRS, mRS 0-2/5-6) compared with patients with pre-stroke mRS 0. RESULTS: We included 1764 patients, of whom 199 (11.3%) had pre-stroke mRS 1-2. No interaction effect of pre-stroke mRS on the relationship between treatment and outcome was observed. Patients with pre-stroke mRS 1-2 had worse outcomes than those with pre-stroke mRS 0 (adjusted common OR (acOR) 0.53, 95% CI 0.40 to 0.70). Nonetheless, a significant benefit of EVT was observed within the mRS 1-2 subgroup (cOR 2.08, 95% CI 1.22 to 3.55). CONCLUSIONS: Patients asymptomatic/without disability prior to onset have better outcomes following EVT than patients with mild disability/symptoms. Patients with pre-stroke mRS 1-2, however, more often achieve good outcomes with EVT compared with conservative management. These findings indicate that mild pre-existing disability/symptoms influence patient prognosis after EVT but do not diminish the EVT treatment effect.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.013 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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 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".