Volumetric magnetic resonance imaging correlates of the National Institute of Neurological Disorders and Stroke–Canadian Stroke Network vascular cognitive impairment neuropsychology protocols
Bibliographic record
Abstract
BACKGROUND: Vascular cognitive impairment (VCI) refers to the entire spectrum of cognitive dysfunction attributable to vascular changes in the brain. The objective of this study is to evaluate magnetic resonance imaging (MRI) correlates of performance on the National Institute of Neurological Disorders and Stroke-Canadian Stroke Network (NINDS-CSN) VCI neuropsychology protocols. METHOD: Fifty ischemic stroke patients and 50 normal elderly persons completed the VCI protocols and MRI. Relationships between the four cognitive domains (executive/activation, language, visuospatial, and memory) and three protocol (60-, 30-, and 5-min) summary scores with MRI measures of volumes of white matter hyperintensities (WMH) and global brain and hippocampal atrophy were assessed using linear regression. RESULTS: All cognitive domain scores were associated with WMH volume and, with the exception of language domain, with global atrophy. Additional relationships were found between executive/activation and language domains with left hippocampal volume, visuospatial domain with right hippocampal volume, and memory domain with bilateral hippocampal volumes. All protocol summary scores showed comparable relationships with WMH and hippocampal volumes, with additional relationships found between the 60- and 30-min protocols with global brain volume. CONCLUSIONS: Performance on the NINDS-CSN VCI protocols reflects underlying volumetric brain changes implicated in cognitive dysfunctions in VCI.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".