Outcome of Stroke Patients with Unknown Onset and Unknown Time Last Known Well Undergoing Endovascular Therapy
Bibliographic record
Abstract
PURPOSE: Endovascular treatment (ET) in patients with large vessel occlusion stroke (LVOS) with unknown onset or an extended time window can be safe and effective if patients are selected by defined clinical and imaging criteria; however, it is unclear if these criteria should also be applied to patients with unknown onset and unknown time last known well. In this study, we aimed to assess whether absent information on the time patients were last known to be well impacts outcome in patients with unknown onset LVOS. METHODS: We analyzed patients who were enrolled in the German Stroke Registry-Endovascular Treatment between 2015 and 2019. Patients with unknown onset and unknown time last known well (LKWu) were compared to patients with known onset (KO) and to patients with unknown onset but known time last known well (LKWk) regarding clinical and imaging baseline characteristics and outcome. RESULTS: Out of 5909 patients, 561 presented with LKWu (9.5%), 1849 with LKWk (31.3%) and 3499 with KO (59.2%). At 90 days, functional independency was less frequent in LKWu (27.0%) compared to KO (42.6%) and LKWk patients (31.8%). These differences were not significant after adjusting for confounders. A main confounder was the initial Alberta stroke program early CT score. CONCLUSION: The LKWu patients had a similar outcome after ET as KO and LKWk patients after adjusting for confounders. Thus, ET should not be withheld if the time last known well is unknown. Instead, LKWu patients may be selected for ET using the same criteria as in LKWk patients.
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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) | 0.001 | 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 | 0.001 |
| 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 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".