Development and validation of the Ascertain Dementia 8 (<scp>AD8</scp>) Thai version
Bibliographic record
Abstract
BACKGROUND: The Ascertain Dementia 8 (AD8) is a brief informant-based questionnaire which reliably distinguishes patients with neurocognitive disorder (NCD) and normal cognition. Our objective was to translate the AD8 into Thai and test its validity as a potentially useful measure to detect patients with the mild stage of major NCD due to Alzheimer disease (major NCD-AD). METHODS: Evaluations of 144 informant-patient dyads were made. Participants were patients who attended the memory clinic at Ramathibodi Hospital and non-patient volunteers. The AD8-Thai version was administered separately from doctor's interviews and neuropsychological assessments. Diagnostic workups included a complete medical history, physical and neurological examinations, neuropsychological testing, the Clinical Dementia Rating Scale-Sum of Boxes (CDR-SOB), Montreal Cognitive Assessment (MoCA), blood tests and brain imaging, preferably with magnetic resonance imaging. All researchers were blinded to the AD8 results. RESULTS: An AD8 score ≥3 had a sensitivity of 95.5%, a specificity of 89.5%, a positive predictive value of 84%, and a negative predictive value of 97.1% for screening major NCD-AD and those with normal cognition. A subgroup analysis with participants aged ≥65 years and with ≥12 years of education revealed comparable ability to the whole group. AD8 scores had a moderate negative relationship with MoCA scores (r = -0.470) and a strong positive relationship with CDR-SOB scores (r = 0.547). The performance of AD8 scores in differentiating mild NCD from normal cognition was not as good as for major NCD-AD. CONCLUSIONS: AD8-Thai version is an acceptable screening tool for major NCD-AD. For patients aged 65 years or older, with at least 12 years of education, and with cognitive complaints in memory clinic, an AD8-Thai score of 3 or more would be sufficient to work on major NCD diagnosis. The performance of the AD8-Thai in mild NCD needs further investigation.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".