Diagnostic value of Montreal Cognitive Assessment in mild cognitive impairment
Bibliographic record
Abstract
Objective To evaluate the diagnostic value of the Montreal Cognitive Assessment(MoCA) in mild cognitive impairment(MCI) by using 25/26 cut-off value with Meta-analysis.Methods PubMed,Medline,VIP,CNKI and WANFANG databases(from January 1 2006 to December 31 2011) were searched to collect studies which evaluated the diagnostic value of MoCA in MCI.The statistical information and quality of science were assessed and classified.The data was analyzed using Meta-Disc1.4 software.The diagnostic value of MoCA in MCI was evaluated by the pooled sensitivity,specificity,and the likelihood ratio.Results Thirteen literatures were collected including 2 in English and 11 in Chinese,and 9 684 subjects were included in the review which were grouped with 6 859 MCI patients and 2 825 cognitive normal individuals,all diagnosed by gold standard.Heterogeneity test showed that the heterogeneity was existed among the study.By using random effects models to analyze the data,the value of the weighted sensitivity was 0.98(95% CI:0.97-0.98),the specificity was 0.55(95% CI:0.53-0.57),the positive likelihood ratio was 3.67(95% CI:2.67-5.05),and the negative likelihood ratio was 0.08(95% CI:0.03-0.18).Conclusion The diagnostic ability of MoCA is good.High sensitivity and low specificity are found by using 25/26 as cut-off value.MoCA could be used as a screening test for MCI screening in Chinese population.Considering its low specificity,more detailed researches should be performed to localize this tool,and focus on its cut-off value establishment.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".