The Consortium to Investigate Vascular Impairment of Cognition: Methods and First Findings
Bibliographic record
Abstract
BACKGROUND: The Consortium to Investigate Vascular Impairment of Cognition (CIVIC) is a Canadian, multi-centre, clinic-based prospective cohort study of patients with Vascular Cognitive Impairment (VCI). We report its organization and the impact of diagnostic criteria on the study of VCI. METHODS: Nine memory disability clinics enrolled patients and recorded their usual investigations and care. A case report form included all vascular dementia (VaD) individual criteria for each of four sets (National Institute of Neurological Disorders and Stroke (NINDS-AIREN), Alzheimer's Disease Diagnostic Treatment Centers (ADDTC), the ICD-10 Classification of Mental and Behavioural Disorders (ICD-10), and the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV)) of consensus-based diagnostic criteria and for the Hachinski Ischemia Score (HIS). Investigators, having completed the case report form, were asked to make a clinical judgement about the cognitive diagnosis based on the best available information, including neuroimaging. RESULTS: Of 1,347 patients (mean age 72 years; 56% women), 846 (63%) were diagnosed with dementia and 324 (24%) were diagnosed with VCI. The proportion of patients diagnosed with VaD by the diagnostic criteria was: 23.9% (n = 322) by DSM-IV, 10.2% (n = 137) by HIS, 4.3% (n = 58) by ICD-10, 3.8% (n = 51) by ADTCC, and 3.6% (n = 48) by NINDS-AIREN. Judged against a clinical diagnosis of VaD, the sensitivity/specificity of each was: DSM-IV (0.77/0.80); HIS (0.41/0.92); ICD-10 (0.29/0.98); ADTCC (0.24/0.98); NINDS-AIREN (0.42/0.995). Compared with a clinical diagnosis of VCI, sensitivities were lower for the diagnostic criteria, reflecting the exclusion of patients who did not have dementia. CONCLUSIONS: Consensus-based criteria for VaD omit patients who do not meet dementia criteria that are modeled on Alzheimer's disease. Even for patients who do, the proportion identified with VaD varies widely. Criteria based on empirical analyses need to be developed and validated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.016 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".