Stroke patients treated by thrombectomy in real life differ from cohorts of the clinical trials: a prospective observational study
Bibliographic record
Abstract
Abstract Background Randomized controlled trials (RCTs) demonstrated efficacy and safety of endovascular treatment (ET) in anterior circulation large vessel occlusions (LVO). We aimed at investigating how stroke patients treated by thrombectomy in clinical practice and their outcome compare to cohorts and results of thrombectomy trials. Methods In a prospective study, we consecutively included stroke patients treated by thrombectomy (2015–2017). Baseline characteristics, procedural and outcome data were analyzed. Outcome was assessed by modified Rankin Scale (mRS) at 90 days. Ordinal regression analysis was performed to identify predictors of outcome. Results Thrombectomy was applied in 264 patients (median 75 years, 49.6% female). Median baseline National Institutes of Health Stroke Scale (NIHSS) was 16, 58.0% received concomitant intravenous thrombolysis, 62.1% were referred from external hospitals. Median Alberta Stroke Program Early CT Score (ASPECTS) was 7. Successful recanalization (modified Thrombolysis in Cerebral Infarction Score, mTICI 2b/3) was achieved in 72.0%. Symptomatic intracranial hemorrhage (sICH) occurred in 4.5%. Independent outcome (mRS 0–2) was achieved in 26.2%, poor outcome (mRS 5–6) in 49.2%. Only 33.5% met the stringent enrolment criteria of previous RCTs. Lower age, baseline NIHSS, pre-stroke mRS, higher ASPECTS, and successful recanalization were independent predictors of favourable outcome. Conclusions The majority of stroke patients treated by ET in clinical practice would not have qualified for randomization in prior RCTs. Outcome in real-life patient cohorts is worse than in the highly selected cohorts from randomized trials, while rates of successful recanalization, sICH and outcome predictors are the same. Our findings support ET in broader patient populations than in the RCTs and may improve treatment decision in individual stroke patients with LVO in clinical practice.
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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 | 0.021 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".