Cognitive tests for the detection of mild cognitive impairment (MCI), the prodromal stage of dementia: Meta‐analysis of diagnostic accuracy studies
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Mild cognitive impairment (MCI) is regarded as a prodrome to dementia. Various cognitive tests can help with diagnosis; meta-analysis of diagnostic accuracy studies would assist clinicians in choosing optimal tests. METHODS: We searched online databases for "mild cognitive impairment" and "diagnosis" or "screening" from 01/01/1999 to 01/07/2017. Articles assessing the diagnostic accuracy of a cognitive test compared with standard diagnostic criteria were extracted. Risk of bias was assessed. Bivariate random-effects meta-analysis was used to evaluate sensitivity and specificity. RESULTS: Eight cognitive tests (ACE-R, CERAD, CDT-Sunderland, IQCODE, Memory Alteration Test, MMSE, MoCA, and Qmci) were considered for meta-analysis. ACE-R, CERAD, MoCA, and Qmci were found to have similar diagnostic accuracy, while the MMSE had lower sensitivity. Memory Alteration Test had the highest sensitivity and equivalent specificity to the other tests. DISCUSSION: Multiple cognitive tests have comparable diagnostic accuracy. The Memory Alteration Test is short and has the highest sensitivity. New cognitive tests for MCI diagnosis should not be compared with the MMSE.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it