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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.002 |
| 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 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".