A comparative study on the validations of three cognitive screening tests in identifying subtle cognitive decline
Bibliographic record
Abstract
BACKGROUND: Subtle cognitive decline (SCD) may represent a very early stage of objective cognitive impairment before mild cognitive impairment (MCI), with less neuronal damage and more functional reservation. Detecting individuals with SCD is imperative for dementia prevention and treatment. In this study, we aimed to compare the validations of three cognitive screening tests, Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment-Chinese Version (MoCA-CV), and Memory and Executive Screening (MES), in identifying subtle cognitive decline. METHODS: A total of 407 individuals were recruited, including 147 cognitively normal controls (NC), 102 individuals with subtle cognitive decline (SCD) and 158 individuals with mild cognitive impairment (MCI) according to the operational neuropsychological criteria proposed by Jak and Bondi's. All participants underwent standardized comprehensive neuropsychological tests and the three cognitive screening tests. Chi-square analysis was used to compare the cognitive performance among the groups of NC, SCD and MCI. Receiver operating characteristic (ROC) curves were used to evaluate the abilities of MMSE, MoCA-CV and MES in discriminating NC, SCD and MCI. RESULTS: Compared with NC, SCD showed a significant decline only in the tests of memory, such as Auditory Verbal Learning Test (AVLT), Rey-Osterrieth Complex Figure Test (CFT) and Prospective Memory Test (PrM) (P < 0.01). However, MCI showed significant decline in all cognitive performances (P < 0.01). The scores of MMSE, MoCA-CV and MES all showed a progressive downward trend within the groups of NC, SCD and MCI (P < 0.001). In ROC Analyses for discriminating individuals with SCD from NC, the most appropriate MES cutoff was 84, with a sensitivity of 74.3%, a specificity of 60.8% and 0.738 for AUC (95%CI, 0.675-0.801). By contrast, MMSE and MOCA-CV had poor sensitivity (67.4 and 70.8%, respectively) and specificity (51.0 and 52.9%, respectively), and smaller AUCs (0.643 and 0.644, respectively) than the MES. CONCLUSION: As a screening test, MES is more efficacious in identifying SCD from normal controls than MMSE and MoCA-CV.
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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 | 0.016 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".