Utility of Psychological Tests in Non-demented Japanese CADASIL Patients
Bibliographic record
Abstract
Introduction Previous studies have reported the usefulness of the Montreal Cognitive Assessment (MoCA) and other psychological tests, primarily in Caucasian patients with cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL). In this study, we evaluated the effectiveness of psychological tests in detecting mild cognitive impairment in Japanese patients with CADASIL, including those with the pro-hemorrhagic subtype associated with the NOTCH3 p.R75P variant. Methods In this single-center prospective study, we examined the utility of the MoCA, Mini-Mental State Examination (MMSE), Trail Making Test (TMT), and the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV). Dementia patients (Clinical dementia rating [CDR]≧1) were excluded. Receiver operating characteristic curves were calculated to examine the sensitivity and specificity of clinical cutoffs for the detection of mild cognitive impairment (CDR=0.5). Results Out of the 61 CADASIL patients who gave written informed consent and visited our clinic between January and December 2022, 51 were included in this study, and 10 were excluded due to CDR≧1. The mean age (standard deviation) was 54 (8), and 28 (55%) were male. The most common mutation was the p.R75P variant, found in 11 patients (22%). Based on the CDR scores, we classified the 51 CADASIL patients into 19 with mild cognitive impairment and 32 without. The ROC analysis showed an area under the curve of 0.90 for MoCA, 0.72 for MMSE, 0.81 and 0.86 for TMT-A and B, and 0.77 and 0.73 for WAIS- IV Digit Span and Digit Symbol. The optimal cut-off values for MMSE and MoCA were 27/28 (sensitivity, 0.58; specificity, 0.84) and 24/25 (sensitivity, 0.74; specificity, 0.97), respectively. Conclusions The MoCA and TMT were found to be sensitive screening tools for detecting mild cognitive impairment in Japanese patients with CADASIL.
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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 | 0.000 | 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) | 0.001 | 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 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".