Conceptualization of mild cognitive impairment: a review
Bibliographic record
Abstract
BACKGROUND: Several factors have prompted renewed interest in the concept of declines in cognitive function that occur in association with aging, in particular the area between normal cognition and dementia. We review the changing conceptualization of what has come to be known as mild cognitive impairment (MCI) in an effort to identify recent developments and highlight areas of controversy. METHODS: Standard MEDLINE search for relevant English-language publications on mild cognitive impairment and its associated terms, supplemented by hand searches of pertinent reference lists. RESULTS: Many conditions cause cognitive impairment which does not meet current criteria for dementia. Within this heterogenous group, termed 'Cognitive Impairment, No Dementia' (CIND), there are disorders associated with an increased risk of progression to dementia. Still, the conceptualization of these latter disorders remains in flux, with variability around assumptions about aging, the relationship between impairment and disease, and how concomitant functional impairment is classified. Amongst patients with MCI, especially its amnestic form, many will progress to Alzheimer's disease (AD). In contrast with clinic-based studies, where progression is more uniform, population-based studies suggest that the MCI classification is unstable in that context. In addition to Amnestic Mild Cognitive Impairment (AMCI), other syndromes exist and can progress to dementia. For example, an identifiable group with vascular cognitive impairment without dementia shows a higher risk of progression to vascular dementia, Alzheimer's disease and mixed dementia. CONCLUSIONS: Recent attempts to profile patients at an increased risk of dementia suggest that this can be done in skilled hands, especially in people whose symptoms prompt them to seek medical attention. Whether these people actually have early AD remains to be determined. The more narrowly defined MCI profiles need to be understood in a population context of CIND.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".