Validation of the Portuguese version of Addenbrooke’s Cognitive Examination III in mild cognitive impairment and dementia
Bibliographic record
Abstract
BACKGROUND: Cognitive assessment is central to the diagnosis of cognitive impairment and dementia, and it should be performed in all patients in the early stages of the disease. Recently, the 3rd version of Addenbrooke's Cognitive Examination (ACE-III) has been developed in order to improve the previous versions. OBJECTIVES: The aim of this study was to determine the psychometric properties of the Portuguese version of ACE-III, namely: reliability and discriminative validity (sensitivity and specificity) in the identification of mild cognitive impairment (MCI) and dementia, in comparison to other neuropsychological screening tests, as well as to establish its concurrent and divergent validity. MATERIAL AND METHODS: The study encompassed a sample of 90 participants distributed into 3 groups: Control (n = 30), MCI (n = 30) and Dementia (n = 30). In addition to ACE-III, Clinical Dementia Rating (CDR) and Montreal Cognitive Assessment (MoCA) were also used. RESULTS: The reliability of ACE-III was very good (α = 0.914). ACE-III significantly differentiated the 3 groups. The receiver operating characteristic (ROC) curves significantly favored ACE-III in comparison to another screening test - MoCA. ACE-III presented higher levels of sensitivity and specificity. Its total score correlated positively with the results on MoCA (ρ = 0.912; p < 0.001) and negatively with a depression scale (ρ = -0.505; p < 0.001). CONCLUSIONS: The Portuguese version of ACE-III has very good reliability and high diagnostic capacity in the context of MCI and dementia. ACE-III also holds concurrent and divergent validity.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".