Abstract WMP8: Use, Characteristics, and Outcomes of Endovascular Thrombectomy in Acute Ischemic Stroke Patients Beyond 6 Hours of Stroke Onset in US Clinical Practice
Bibliographic record
Abstract
Introduction: Two recent RCTs have shown benefit of endovascular thrombectomy (EVT) in acute ischemic stroke (AIS) 6-24 h from last known well (LKW) using imaging-guided patient selection, however little is known about outcomes in contemporary non-trial settings. We assessed the frequency and outcomes of EVT beyond 6 h in the US national GWTG-Stroke clinical registry. Methods: We analyzed all AIS hospitalizations between 1/1/09 - 10/1/18 at fully participating GWTG-Stroke sites to identify 53,702 patients at 697 sites treated with EVT (± IV tPA) who had valid LKW, symptom discovery (SxD) and treatment times recorded. Hospital characteristics were analyzed at the 470 sites that treated > 10 patients during the study. Table 1 shows significant covariates (standardized differences >10%) and adjusted outcomes based on logistic regression models. Results: Treatment >6 h from LKW occurred in 33% of all EVT cases (median 4.7 h, IQR 3.3-7 h), and all were treated <6 h from SxD. The proportion of EVT cases treated >6 h from LKW varied widely across sites (median 30%, IQR 24-38%) and increased sharply in 2018 (Fig). Compared to < 6 h, patients treated >6 h differed in age, AF, arrival mode/time, stroke severity and use of anticoagulation, and presented to higher EVT volume centers. Late window EVT patients had less favorable adjusted outcomes at discharge for mortality, ambulation and disposition to home or IRF compared to <6 h patients (Table). Conclusions: EVT is frequently performed >6h, accounting for one-third of cases nationally. As adjusted functional outcomes at discharge are worse in these patients, further research is required to ensure optimal EVT outcomes in clinical practice settings
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".