Consensus-Harmonized Neuropsychological Assessment for Vascular Cognitive Impairment and Dementia
Bibliographic record
Abstract
Importance: Harmonization of neuropsychological assessment for vascular cognitive impairment and dementia (VCID) is important for ensuring the highest standards and consistency of diagnosis. A battery proposed in 2006 by the National Institute for Neurological Disorders and Stroke and the Canadian Stroke Network (NINDS-CSN) has received much international support. Considering significant advances in the field, including the rise of computerized and remote assessment methods, a revision is needed. Objective: To develop an updated harmonized battery and associated assessment guidelines for VCID. Evidence Review: NINDS-CSN and other relevant published harmonized neuropsychological batteries, aided by literature review of recent developments in VCID, were used as reference points for an online Delphi survey (≥3 rounds, ≥75% threshold for agreement), including questions on a core test battery based on key cognitive domains that should be assessed for VCID, consideration of computerized and remote assessment methods, and assessment of diverse populations. International experts in neuropsychological assessment from diverse international regions were invited to participate in 2023. Data were analyzed from October 11, 2023, to June 20, 2024. Findings: A total of 44 experts participated in 3 survey rounds, with 28 to 31 participants each. Consensus was reached on a core assessment battery of neuropsychological tests based on key cognitive domains, and additional guidelines for a more comprehensive test battery, cognitive screening, telehealth and computerized assessment methods, principles for normative standardization, and the assessment of diverse populations. The key cognitive domains were harmonized with the International Society for Vascular Behavioural and Cognitive Disorders version 2 World Stroke Organization (VasCog-2-WSO) diagnostic criteria for VCID. Conclusions and Relevance: This consensus statement describes the development of a harmonized neuropsychological assessment battery and guidelines for VCID (VasCog-NP) that expands on the NINDS-CSN battery with more comprehensive and flexible assessment of VCID. Harmonized with the VasCog-2-WSO diagnostic criteria, VasCog-NP could be adopted internationally to further help more consistent neuropsychological evaluations related to VCID, facilitating global comparisons for clinicians and researchers.
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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 | 0.287 | 0.315 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.006 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.007 | 0.014 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".