Distribution and prognosis of acute ischaemic stroke with negative diffusion-weighted imaging
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: To examine the distribution and prognosis among patients with diffusion-weighted imaging (DWI)-negative acute ischaemic stroke (AIS) and explore the differences between mild (National Institute of Health Stroke Scale (NIHSS) score ≤5) and major (NIHSS score >5) ischaemic stroke in DWI-negative patients. METHODS: Patients with AIS with baseline DWI from the Third China National Stroke Registry (CNSR-III), based on a prospective, observational, multicentre cohort study, between August 2015 and March 2018, were included. Patients were classified into negative and positive DWI groups depending on the existence of acute lesions on DWI. RESULTS: Among 12 026 patients who had an ischaemic stroke, 932 (7.7%) had negative DWI. As the NIHSS score increased, the proportion of patients with DWI-negative AIS gradually decreased. Negative DWI was associated with a decreased risk of stroke recurrence (HR 0.63, 95% CI 0.49 to 0.82), combined vascular events (HR 0.72, 95% CI 0.56 to 0.92), mortality (HR 0.60, 95% CI 0.36 to 0.995) and poor functional outcomes (OR 0.57, 95% CI 0.43 to 0.76) within 1 year in all patients. Similar associations were observed in patients with mild AIS (p<0.05 for all) but not in patients with major AIS, excluding poor functional outcomes (OR 0.47, 95% CI 0.28 to 0.81). CONCLUSIONS: The proportion of patients with DWI-negative AIS gradually decreased as the NIHSS score increased, and negative DWI was mainly observed in patients with mild AIS. Negative DWI was associated with a better prognosis for all patients with AIS. However, these associations were significant for mild AIS but not for those with major AIS.
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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".