Usefulness of the japanese version of rapid dementia screening test for mild cognitive impairment in older patients with cardiovascular disease
Bibliographic record
Abstract
Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): JSPS KAKENHI Background Cognitive decline is common among older patients with cardiovascular disease and can decrease their self-management abilities. Therefore, early detection of cognitive decline is clinically important, as it can help guide effective home-based care measures, including education of family members and deployment of healthcare resources. However, the standard instruments for identifying mild cognitive impairment (MCI) are not always feasible in clinical practice. Purpose This study evaluated whether MCI could be detected using the Japanese version of the Rapid Dementia Screening Test (RDST-J), which is a simple screening tool for identifying cognitive decline. Methods This cross-sectional study included patients who were ≥ 65 years old and hospitalised because of cardiovascular disease. Patients with a pre-hospitalisation diagnosis of dementia were excluded. Each patient’s cognitive function had been measured at discharge using the RDST-J and the Japanese version of the Montreal Cognitive Assessment (MoCA-J), which is a standard tool for MCI screening. The RDST-J includes a number transcoding task and a supermarket task, and can be completed in 3 min (range: 0–12 points). The MoCA-J assesses nine domains of cognition and requires 10–15 min to complete (range: 0–30 points). The correlation between the two scores was evaluated using Spearman’s rank correlation coefficient. Receiver operating characteristic (ROC) analysis was also conducted to evaluate whether the RDST-J could identify MCI, which was defined as a MoCA-J score of ≤ 25 points. Results The study included 78 patients (the mean age: 77.2 ± 8.9 years, men: 56.4%). Based on a MoCA-J score of ≤ 25 points, MCI was identified in 73.1% (n = 57) of the patients. The RDST-J and MoCA-J scores were strongly correlated (r = 0.835, p <0.001). The ROC analysis revealed that an RDST-J score of ≤ 9 points provided 75.4% sensitivity and 95.2% specificity for identifying MCI, with an area under the curve of 0.899 (95% confidence interval: 0.835–0.964, Figure 1). The same cut-off value was identified when excluding patients with a high probability of dementia (RDST-J score of ≤ 4 points). Conclusions The RDST-J is a simple instrument and its score was highly correlated with the standard test for identifying MCI in older patients with cardiovascular disease. Our results suggest that the RDST-J may be useful for routine cognitive assessments in clinical practice. Longitudinal studies are needed to evaluate whether the RDST-J scores respond to changes in cognitive status, as well as whether this tool can be used to predict adverse health outcomes after discharge.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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".