Implications of limiting mechanical thrombectomy to patients with emergent large vessel occlusion meeting top tier evidence criteria
Bibliographic record
Abstract
BACKGROUND: Recent guidelines for endovascular management of emergent large vessel occlusion (ELVO) award top tier evidence to the same selective criteria in recent trials. We aimed to understand how guideline adherence would have impacted treatment numbers and outcomes in a cohort of patients from a comprehensive stroke center. METHODS: A retrospective observational study was conducted using consecutive emergent endovascular patients. Mechanical thrombectomy (MT) was performed with stent retrievers or large bore clot aspiration catheters. Procedural outcomes were compared between patients meeting, and those failing to meet, top tier evidence criteria. RESULTS: 126 patients receiving MT from January 2012 to June 2015 were included (age 31-89 years, National Institutes of Health Stroke Scale (NIHSS) score 2-38); 62 (49%) patients would have been excluded if top tier criteria were upheld: pretreatment NIHSS score <6 (10%), Alberta Stroke Program Early CT score <6 (6.5%), premorbid modified Rankin Scale (mRS) score ≥2 (27%), M2 occlusion (10%), posterior circulation (32%), symptom to groin puncture >360 min (58%). 26 (42%) subjects had more than one top tier exclusion. Symptomatic intracerebral hemorrhage (sICH) and systemic hemorrhage rates were similar between the groups. 3 month mortality was 45% in those lacking top tier evidence compared with 26% (p=0.044), and 3 month mRS score 0-2 was 33% versus 46%, respectively (NS). After adjusting for potential confounders, top tier treatment was not associated with neurological improvement during hospitalization (β -8.2; 95% CI -24.6 to -8.2; p=0.321), 3 month mortality (OR=0.38; 95% CI 0.08 to 1.41), or 3 month favorable mRS (OR=0.97; 95% CI 0.28 to 3.35). CONCLUSIONS: Our study showed that with strict adherence to top tier evidence criteria, half of patients may not be considered for MT. Our data indicate no increased risk of sICH and a potentially higher mortality that is largely due to treatment of patients with basilar occlusions and those treated at an extended time window. Despite this, good functional recovery is possible, and consideration of MT in patients not meeting top tier evidence criteria may be warranted.
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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 | 0.002 | 0.033 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".