The Role of Functional Assessment as an Outcome Measure in Antidementia Treatment
Bibliographic record
Abstract
Functional assessment refers to the evaluation of performance in basic activities of daily living, instrumental activities of daily living, professional duties, and hobbies. This assessment is particularly relevant in the evaluation of cognitive impairment. In fact, functional decline represents a core feature of dementia according to the DSM-IV criteria. Clinically, functional deterioration represents a diagnostic marker, can be used to chart the course of the disease, and as a prognostic marker as it contributes significantly to caregiver burden and institutionalization. For all these reasons, functional assessment has been widely used as an outcome measure in intervention trials of Alzheimer disease (AD). Appropriate function assessment scales have been developed for use in clinical trials of AD. Studies have shown that functional decline benefits from pharmacological interventions in AD and some other cognitive syndromes. This benefit translates into a stabilization ranging between 6 to 12 months compared to a gradual deterioration in the placebo group. There is rarely reversibility for IADL's lost. There are no functional scales specifically designed for assessment of subjects with non-AD cognitive impairment. Scales specifically developed for Mild Cognitive Impairment and other dementias are needed.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".