Endovascular treatment results in patients with large cerebral artery occlusions in a metropolis. Moscow Stroke Registry data over 2019
Bibliographic record
Abstract
Objective : to assess results from the Stroke Network created on the basis of the Infarction Network in the metropolis Moscow for endovascular treatment in patients with occlusion of the large cerebral artery (the internal carotid artery, the M1 and M2 segments of the middle cerebral artery, and the main artery). Patients and methods . A total of 742 thromboextractions were performed in patients with ischemic stroke in Moscow Stroke Network hospitals in 2019. The final analysis included 729 patients aged 25 to 97 years (mean age, 71 years); of them there were 370 (50.8%) men and 359 (49.2%) women. The selection criteria for endovascular treatment for ischemic stroke were consistent with those set out in the 2015 American Heart Association/American Stroke Association (AHA/ASA) guidelines, which included a pre-stroke modified Rankin Scale (MRS) score of 0–1; ≥18 years of age; a National Institutes of Health Stroke Scale (NIHSS) score of ≥6; and an Alberta Stroke Programme Early CT score (ASPECTS) ≥6. The angiographic results were assessed using the Thrombolysis in Cerebral Infarction (TICI) scale. The clinical outcomes were measured with the NIHSS and the MRS. Results and discussion . Successful recanalization (TICI 2b/3) was achieved in 547 (75%) patients. The predominant technique for thromboextraction was thromboaspiration that was used in 376 (51.6%) patients. Combined procedures (the co-use of an aspiration catheter and a stent retriever) were the second most commonly used – in 231 (31.7%) patients. By the end of the 20th day, good functional recovery (MSR 0–2 scores) was observed in 213 (29.2%) patients. The 20-day mortality rate was 31.8%. Conclusion . The successfully functioning Infarction Network in Moscow was used to create the Stroke Network for treatment in patients with ischemic stroke and large cerebral artery occlusion, the clinical results of which are comparable to large European registry studies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".