Endovascular Therapy in Large Core Ischemic Strokes: Real-World Indian Experience
Bibliographic record
Abstract
BACKGROUND: Large core acute ischemic strokes have predominantly been excluded from endovascular therapy (EVT) studies due to perceived higher risks of hemorrhage and poorer functional outcomes. However, recent randomized controlled trials (RCTs) indicate that EVT for large vessel occlusion (LVO) strokes improves functional outcomes compared to medical management alone, despite higher hemorrhagic transformation rates, with no corresponding increase in symptomatic intracerebral hemorrhage (sICH) rates. The real-world outcomes of this intervention in Indian patients remain underexplored. OBJECTIVES: To evaluate the real-world outcomes of EVT for large core acute ischemic strokes with LVO in an Indian population. METHODS: We conducted a single-center, retrospective observational study using a 7 years prospective database of EVT in anterior circulation stroke patients. Patients with Alberta Stroke Program Early Computed Tomography Score (ASPECTS) of 3-5 were included. Clinical and radiologic data were analyzed, with the primary endpoint being 90-day modified Rankin scale (mRS) scores. Safety outcomes included rates of sICH and mortality. Descriptive statistical analysis was done using Microsoft Excel. RESULTS: The study included 25 patients who met the inclusion criteria. Mean age of patients was 52.9 ± 14.3 years, and there were 13 (52%) males. Median ASPECTS was 5 (interquartile range 4-5). Successful recanalization, classified by modified Thrombolysis in Cerebral Infarction score, was 92%. Good functional recovery, that is, 90-day mRS 0-3, was achieved in nine (36%) patients. Safety outcomes: sICH was seen in four (16%) and mortality was reported in nine (36%) patients. CONCLUSIONS: Our results reaffirm findings from RCTs, provide updated real-world evidence, and suggest that EVT is a viable option to be considered in selected patients with large core ischemic infarcts.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".