Abstract T P105: Cognitive Impairment is Common After Both Lacunar and Non-Lacunar Stroke and Persists at One Year
Bibliographic record
Abstract
Background: Few data exist on long term cognitive outcome after lacunar stroke. We assessed cognition 1-6 weeks and 1 year after lacunar and mild cortical stroke, whilst correcting for age, SVD, depression and pre-morbid IQ. Methods: We recruited consecutive patients with lacunar and mild cortical stroke, diagnosed with DWI-MRI and careful clinical assessment. At 4-6 weeks and 1 year after index stroke we assessed white matter hyperintensities (WMH; Fazekas scale), cognition (Addenbrookes Cognitive Assessment, ACE-R), pre-morbid IQ (National Adult Reading Test, NART) and depression (Beck Depression Index, BDI). We defined 'dementia' as an ACE-R<88. Results: At 4-6 weeks post-stroke, 61/157 (38%) had dementia; at 1 year 56/151 (37%) had dementia; 136 were tested twice. Of the 45 who had dementia at first assessment & 9(20%) no longer had dementia at 1 year; of the 91 who did not have dementia at 4-6 weeks, 13 (14%) had become demented by 1 year. Patients with lacunar stroke had similar risk of cognitive impairment as patients with cortical stroke when adjusted for age, Fazekas score, BDI and NART in multivariable analyses (OR 0.91, 95%CI 0.32-2.13 at 1st assessment & 0.81, 95%CI 0.46-2.27 at 1 year). Previous stroke, low pre-morbid IQ and depression increased risk of dementia at both time points, but not vascular risk factors, sex, NIHSS or Fazekas score. Conclusion: Over one third of patients with a non-disabling stroke had dementia at 4-6 weeks post stroke, most of these (80%) remained demented at one year and 13% of those who were cognitively intact ay 4-6 weeks developed dementia by 1 year. Patients with lacunar stroke are equally likely to have dementia as those with cortical stroke, despite the small lesion size and good prognosis. Low pre-morbid IQ increases dementia risk. Future research should account for pre-morbid IQ, age and depression.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".