Bibliographic record
Abstract
Abstract: The term vascular cognitive impairment (VCI) is now employed to capture the spectrum of illness and disability arising from impaired cognitive function of vascular origin. As such, it supplants the more narrowly focussed terms “Vascular dementia (VaD)” and “multi‐infarct dementia”. It is meant to include both those whose cognitive impairment is different from that assumed by the usual criteria for dementia. Traditionally, dementia criteria have been modelled on AD, a disorder with more characteristic neuropathological and clinical disease expression than is seen in VaD, which can occur in many forms. VCI is common, and is associated with many adverse outcomes, including worse cognition, institutionalization, and death. One form of VCI is coincident AD and VaD, a category which, although it has been comparatively neglected, may be amongst the most common forms of dementia. Another common form of VCI has a predilection for subcortical ischemic lesions, and for a clinical presentation which reflects frontal and subcortical involvement. At present, there is no specific treatment for VCI, although several agents appear to offer the hope of both treatment and prevention. Further research on the clinical, pathological and mechanistic underpinnings of this important syndrome is needed. For a long time, VaD has been recognized as the second most common cause of dementia.1,2) More recently, however, the concept of cognitive impairment in relation to cerebrovascular disease has been expanded. This paper will review the notion of “vascular cognitive impairment” (VCI) as it relates to clinical practice, and to our understanding of disease mechanisms in dementia and related disorders. It will propose that while the expanded concept has merit, within it are to be found distinct subgroups, including some of particular importance as targets for clinical trials of therapeutic and even preventive interventions.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.065 | 0.016 |
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".