Endovascular Thrombectomy Eligibility in the 0-24-Hour Time Window at a Large Academic Center in India
Bibliographic record
Abstract
Background: The data regarding patients eligible for endovascular thrombectomy (EVT), especially in the developing world is lacking. Objective: To determine the proportion of patients with acute ischemic stroke (AIS) who are eligible for EVT in the 0-24-h time window. Materials and Methods: We performed a retrospective cohort study using prospectively collected AIS data between July 2017 and September 2019. Demographic, clinical, and management information were analyzed. EVT eligibility was explored using the following criteria: National Institutes of Health Stroke Scale (NIHSS) score ≥6, presence of anterior circulation large-vessel occlusion (ACLVO), Alberta stroke program early Computerized Tomography score (ASPECTS) ≥6, baseline modified Rankin Scale (mRS) score 0-2, and within 24 h of time last seen well (TLSW). EVT-eligible patients were further evaluated for in-hospital course and outcomes. Results: In the study period of 27 months, there were 221 patients with AIS who presented within 24 h. The mean age of the patients was 54.4 (16.0) years and 66.1% (146) were males. A majority (61.5% [136/221]) arrived within 6 h of TLSW. Of these, 81.6% (111/136) presented in the time window for thrombolysis (0-4.5 h). The patients with NIHSS ≥6 and ACLVO constituted 41.2% (91/221) of the patients. AIS eligible for EVT constituted 19.5% (43/221) of the patients. Conclusion: In our study, the proportion of AIS eligible for endovascular thrombectomy was comparable to the developed world. These data predict a large potential for the late-window EVT in India.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".