Bridging therapy is associated with improved cognitive function after large vessel occlusion stroke – an analysis of the German Stroke Registry
Bibliographic record
Abstract
Abstract Background The targeted use of endovascular therapy (EVT), with or without intravenous thrombolysis (IVT) in acute large cerebral vessel occlusion stroke (LVOS) has been proven to be superior compared to IVT alone. Despite favorable functional outcome, many patients complain about cognitive decline after EVT. If IVT in addition to EVT has positive effects on cognitive function is unclear. Methods We analyzed data from the German Stroke Registry (GSR, an open, multicenter and prospective observational study) and compared cognitive function 90 days after index ischemic stroke using MoCA in patients with independent (mRS ≤ 2 pts) and excellent (mRS = 0 pts) functional outcome receiving combined EVT and IVT (EVT + IVT) vs. EVT alone (EVT-IVT). Results Of the 2636 GSR patients, we included 166 patients with mRS ≤ 2 at 90 days in our analysis. Of these, 103 patients (62%) received EVT + IVT, 63 patients (38%) were treated with EVT alone. There was no difference in reperfusion status between groups (mTICI ≥ 2b in both groups at 95%, p = 0.65). Median MoCA score in the EVT + IVT group was 20 pts. (18–25 IQR) vs. 18 pts. (16–21 IQR) in the EVT-IVT group ( p = 0.014). There were more patients with cognitive impairment (defined as MoCA < 26 pts) in the EVT-IVT group (54 patients (86%)) compared to the EVT + IVT group (78 patients (76%)). EVT + IVT was associated with a higher MoCA score at 90 days (mRS ≤ 2: p = 0.033, B = 2.39; mRS = 0: p = 0.021, B = 4.38). Conclusions In Patients with good functional outcome after LVOS, rates of cognitive impairment are lower with combined EVT and IVT compared to EVT alone. Trial registration ClinicalTrials.gov Identifier: NCT03356392 .
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".