Cognitive test norms and comparison to normal cognition and mild cognitive impairment: A population‐based study among community‐dwelling Filipinos
Bibliographic record
Abstract
Abstract Background Clinicians use neuropsychological assessment to screen individuals for cognitive impairment since it more convenient and can detect impaired parts of cognition to provide early treatment. This study is aimed to differentiate the cognitive performance on the Alzheimer’s Disease Assessment Scale – Cognition (ADAS‐Cog) among the older adults with normal cognition and with MCI. Method The sample composed of 302 participants aged ≥60 years old who met the score of 25 in the Mini‐mental status examination (MMSE). Psychologists would then administer cognitive measures (ADAS‐Cog, logical memory recognition and delayed recall, verbal fluency on animals and vegetables, digit span forward and backward, digit symbol, and trailmaking A and B) upon meeting. ADAS‐Cog total and subtest scores were compared across the two groups. Receiver operating characteristics (ROC) analysis were performed and, sensitivity and specificity were calculated. Result Most of the participants are female (81.8%) compared to males (17.9%). 64.2% has normal cognition while 35.8% of them have MCI. The mean age was 69.16 (±5.77) years and mean years of education of 9.11 (±3.57). The MCI group they have a cut‐off ADAS‐Cog score of 13.57(±5.49) (sensitivity= 0.63; specificity= 0.69) while the normal group have a score of 9.96 (±4.79). It also showed significant difference (t=5.971; p≤0.01) among the groups; domains showed a significant relationship i.e.: word list recall, naming, commands, ideational praxis, orientation, word list recognition (p≤0.01) and constructional praxis (p=0.015). Other cognitive measures besides digit symbol (t=1.578; p=0.116) are significant i.e. logical memory recognition and recall, verbal fluency on animals and vegetables, digit span forward and backward, and trailmaking A and B (p≤0.01). Conclusion The ADAS‐Cog is inapplicable as a screening tool for MCI but specific for MCI diagnosis. There is significant difference found between functional impairment among MCI and normal cognition in the overall and subtests scores.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".