Unknown‐onset strokes with anterior circulation occlusion treated by thrombectomy after DWI‐FLAIR mismatch selection
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The DAWN trial recently showed compelling evidence in treating late window and wake-up stroke patients with thrombectomy using a clinical-imaging mismatch. The aim was to evaluate the results of thrombectomy for unknown-onset strokes (UOS) treated in our centres after a diffusion weighted imaging/fluid attenuated inversion recovery (DWI-FLAIR) mismatch based selection. METHODS: A multicentre, cohort study was performed of consecutive UOS treated by thrombectomy between 2012 and 2016. UOS with proximal anterior circulation occlusion discovered beyond 6 h from 'last seen normal' were compared with known-onset strokes (KOS) for whom thrombectomy was started within 6 h from onset. Time intervals were recorded from first time found abnormal. Results were adjusted for age, diabetes, hypertension, National Institutes of Health Stroke Scale, site of occlusion, DWI Alberta Stroke Programme Early CT Score, intravenous thrombolysis and use of general anaesthesia. RESULTS: Amongst 1246 strokes with anterior circulation occlusion treated by thrombectomy, 277 were UOS, with a 'last time seen well' beyond 6 h and DWI-FLAIR mismatch, and 865 were KOS who underwent groin puncture within 6 h. Favourable outcome was achieved less often in UOS than KOS patients (45.2% vs. 53.9%, P = 0.022). After pre-specified adjustment, this difference was not significant (adjusted relative risk 0.91; 95% confidence interval 0.80-1.04; P = 0.17). No differences were found in secondary outcomes. Time intervals from first found abnormal were significantly longer in UOS. CONCLUSION: Thrombectomy of UOS with anterior circulation occlusion and DWI-FLAIR mismatch appears to be as safe and efficient as thrombectomy of KOS within 6 h from onset. This pattern of imaging could be used for patient selection when time of onset is unknown.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".