Endovascular Treatment of Ischemic Stroke in a Developing Country
Bibliographic record
Abstract
Background: There is inequality in access to recent advancements in endovascular treatment of acute ischemic stroke (AIS), and Mexico is unusually sensitive to such inequality. Aims: To report the initial experience of the Mexican Endovascular Reperfusion Registry (MERR). Methods: The MERR is an academic, independent, prospective, multicenter, observational registry of patients treated with endovascular reperfusion techniques in Mexican hospitals. The registry includes information on demographic and clinical characteristics, diagnostic procedures, treatments, selected time metrics, and outcomes. Results: In all, 49 (57.1% female) patients from 8 centers were included and had the following characteristics: median National Institute of Health Stroke Scale score, 16; median Alberta Stroke Program Early CT Score score, 9; received intravenous tissue-type plasminogen activator, 49%; and treated with mechanical devices, 39 (79.6%), including 20 treated with stent retriever alone, 2 with retriever and intra-arterial thrombolysis (IAt), 10 with catheter aspiration (4 in combination with IAt), 6 with a combination of catheter aspiration and stent retriever, and 1 with IAt followed by balloon angioplasty. Recanalization (TICI 2b or better) was achieved in 69.4% of the patients. The median clot to recanalization time was 30 minutes. A modified Rankin scale ≤2 was achieved in 44.9% of the patients, and 68.2% of these were treated with stent retriever ( P = .011). Procedure-related morbidity was 12.2%, 7 patients presented intracerebral hemorrhage (71.4% asymptomatic), and all-cause mortality was 6.1%. Conclusions: Endovascular treatment of AIS in Mexico is feasible and has an efficacy comparable to that of other countries. Still, many challenges remain, especially pertaining to high costs and difficulties in equality in access to treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".