Differences in Wake-up and Unknown Onset Stroke Examined in a Stroke Registry
Bibliographic record
Abstract
INTRODUCTION: Debate exists as to whether wake-up stroke (WUS) (i.e. symptoms first noted on waking) differs from stroke developing while awake [awake onset stroke (AOS)]. Unknown onset stroke (UOS) with unclear symptom onset time is infrequently studied. AIMS: This study aimed to examine differences in stroke characteristics and outcomes in these three groups. METHODS: The stroke registry database from Halifax Infirmary, Canada, was interrogated for hospitalised stroke patients between 1999-2011. Information was available on demographics, stroke characteristics, and functional status at discharge and six months (modified Rankin score [mRS]). RESULTS: Of 3890 patients, 65% had AOS, 21% WUS and 14% UOS. UOS patients were significantly older, more commonly female and living alone than AOS patients, with no difference between AOS and WUS. UOS rates increased from 10 to 16% of patients during the study period (P < 0.0001). UOS but not WUS had a higher stroke severity than AOS. Intracerebral hemorrhage was less common (9 vs. 13%) and lacunar stroke more common (23 vs. 19%) in WUS compared to AOS. In UOS left hemisphere location was more likely, and lacunar stroke less common. Excellent outcomes were slightly lower for WUS. UOS had significantly higher rates of in-hospital mortality (23 vs. 16%, P < 0.0001) and poorer functional outcome six months after stroke (mRS < 3 in 26% of UOS and 46% of AOS, P = 0.02). CONCLUSION: WUS has lower rates of ICH but similar stroke severity and outcomes to AOS. UOS prevalence appears to be increasing, with higher stroke severity and worse prognosis.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".