P2‐018: Cognitive correlations of stroke, white matter disease and brain atrophy after stroke: Preliminary validation of NINDS‐VCI harmonization criteria
Bibliographic record
Abstract
Vascular Cognitive Impairment (VCI) is very common, but relationships between focal stroke, white matter hyperintensities(WMH), brain atrophy, and cognition are poorly understood. We investigated this using neuropsychological and MRI acquisition protocols recommended by the recent VCI harmonization criteria. (Hachinski,2006). Twenty participants, 6-18 months post-infarct were scanned at 3-Tesla (3D-T1, PD/T2 and FLAIR sequences). Brain tissue segmentation, and regional parcellation, separate WMH analysis (Levy,2008) and stroke lesion tracing were performed. The stroke mask was flipped to the contralateral hemisphere to estimate tissue compartment loss. Volumes were divided by total intracranial capacity to correct for head size. Total and domain z scores were computed for the VCI 60 and 30 minute protocols, testing executive, language, visuospatial and memory. The Montreal Cognitive Assessment and 5 minute battery scores served as screening batteries. Demographics were summarized by the BARONA score (weighted for age, education, SES, ethnicity and sex), which was forced into linear multiple regressions, followed by normalized volumetric measures, (eg brain parenchymal fraction(BPF), WMH and stroke volumes) to predict cognitive performance. Means for 20 subjects (13 women) were: age=65.9; YOE=12.5; MMSE=27; infarct volume=14.9 cm3(14 left-sided); WMH volume=11.7 cm3. BARONA only contributed significantly (R2=0.3,p<0.05) in a linear regression model predicting executive function. BPF improved the models significantly over BARONA alone for the 60 and 30 minute (both R2 change=0.3,p<0.01), and for the memory scores (R2 change=0.4,p<0.05) in multiple regression models, but not for the screening batteries. WMH and infarct volumes did not contribute, except for left dorsolateral frontal WMH volume which added significantly to the variance with BARONA, explaining the executive domain tasks (R2 change=0.3,p<0.01). A method was developed to combine brain tissue volumetrics and lesion tracing to test validity of VCI harmonization protocols in exploring brain-behaviour relationships post-stroke. After accounting for demographic factors, global brain volume best predicted overall cognitive scores in the longer batteries, while the left dorsolateral frontal WMH volume was associated with executive deficits. The preliminary analysis indicates that the recommended batteries correlate with relevant brain measures in a VCI population and as the sample accrues, more specific relationships (eg stroke volume, regional tissue volumes) are being investigated with ongoing support of NIH.
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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 | 0.010 | 0.014 |
| 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 | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".