Revised Diagnostic Criteria for Vascular Cognitive Impairment and Dementia—The VasCog-2-WSO Criteria
Bibliographic record
Abstract
Importance: Several sets of diagnostic criteria have been proposed for vascular cognitive impairment and dementia (VCID). The International Society for Vascular Behavioural and Cognitive Disorders (VasCog) working group published comprehensive operationalized criteria in 2014. Considering subsequent advances in the field, a revision was needed. Objective: To update the VasCog criteria to achieve consensus on diagnosis of VCID. Design, Setting, and Participants: VasCog criteria and other published diagnostic guidelines, aided by literature review of recent developments in VCID, were used as reference points for an online Delphi survey (minimum 3 rounds, ≥75% threshold for agreement), including operationalization of criteria and guidance on potential biomarkers. Seventy international experts from diverse international regions were invited to participate in 2023. Results: Three survey rounds included 49 to 54 participants that agreed on VasCog-2 diagnostic criteria for preclinical, mild, and major dementia levels of vascular cognitive impairment (under the overarching term VCID). Research guidelines, including the use of novel neuroimaging and fluid biomarkers, were also agreed on. The World Stroke Organization (WSO) endorsed the criteria, hence named VasCog-2-WSO. Conclusions and Relevance: The VasCog-2-WSO criteria update the VasCog criteria for the diagnosis of VCID, providing operationalization and additional guidance on potential neuroimaging and fluid biomarkers. VasCog-2-WSO should provide an international standard for VCID diagnosis, facilitating diagnostic consistency among 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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| 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".