Systematic review of the diagnostic accuracy of the non-English versions of Addenbrooke's cognitive examination – revised and III
Bibliographic record
Abstract
OBJECTIVE: This systematic review aims to review the evidence for the diagnostic accuracy of the non-English updated versions of Addenbrooke's Cognitive Examination (ACE) - the ACE-Revised (ACE-R) and the ACE-III - in the diagnosis of dementia. METHODS: A systematic search resulted in 16 eligible studies evaluating the diagnostic accuracy of ACE-R and ACE-III in ten different languages. Most studies were assessed as of medium to low quality using Standards for Reporting of Diagnostic Accuracy (STARD) guidance. RESULTS: The findings of excellent diagnostic accuracy are compromised by the methodological limitations of studies. While studies generally reported excellent diagnostic accuracy across and within different languages, optimal cut-offs even within particular language versions, varied. CONCLUSION: There is a need for future research to address these limitations through adherence to STARD guidelines. The ACE-III is particularly under-evaluated and should be a focus of future research. The variance in obtained optimal cut-offs within language versions is an issue compromising clinical utility and could be addressed in future work through use of a-priori defined thresholds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".