Comparison of Rapid Cognitive Screen against Montreal Cognitive Assessment in screening for cognitive impairment in the old and old‐old
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The Montreal Cognitive Assessment (MoCA) was developed as a screening tool for mild cognitive impairment (MCI). Given the need for a rapid screening test in settings such as primary care, we compare the validity of the Rapid Cognitive Screen (RCS) against the MoCA, and determine cut-off scores in the old and old-old. METHODS: Cross-sectional study involving community-dwelling 'old' (65 to 79 years old) and 'old-old' (≥ 80 years old) without dementia. Cognitive impairment was defined by MoCA score 17 to 22. Validation was done using the receiver operating characteristic (ROC) curve analysis: area under the curve (AUC), sensitivity (Sn), and specificity (Sp). RESULTS: Of the 183 participants (mean age 72.1 ± 5.2 years),15.8% (n = 29) were classified as cognitively impaired. The overall ROC curve had an AUC of 0.82 (95% CI 0.75-0.90, P < 0.01) with an optimal cut-off of 7/8 on RCS (Sn 0.77, Sp 0.72). The 'old' and 'old-old' group had AUC of 0.82 (95% CI 0.74-0.91, P < 0.01) with 8/9 as optimal cut-off (Sn 0.51, Sp 0.96) and AUC of 0.85 (95% CI 0.66-1.03, P < 0.01) with 7/8 as optimal cut-off (Sn 0.71, Sp 1.00) respectively. In multivariate analysis, age was associated with 0.05 (95% CI -0.10-0.00, P < 0.04) point decrement, while >6 years of education was associated with 0.82 (95% CI 0.32-1.33, P < 0.01) point increment in RCS scores. CONCLUSION: The three-item RCS is quick and easy to administer. Although RCS met the criterion for good validity against MoCA in predicting cognitive impairment, its utility as a first-line screening tool needs to be further validated in a large-scale population study.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it