The Clinical Utility of the TYM and RBANS in a One-Stop Memory Clinic in Singapore: A Pilot Study
Bibliographic record
Abstract
Background: We aimed to examine the discriminant validity of a brief self-administered cognitive screening test, the Test Your Memory (TYM) and a brief neuropsychological test, the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), supplemented with executive and language tests (Color Trail Test [CTT] and modified Boston Naming Test [mBNT], respectively), in detecting cognitive impairment (CI) in a one-stop memory clinic in Singapore. Methods: Ninety patients ≥50 years old with a diagnosis of no cognitive impairment, mild cognitive impairment, and mild Alzheimer disease were recruited from memory clinic. They received the TYM, Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), RBANS, CTT, mBNT, and a gold-standard formal neuropsychological test battery. Results: The TYM had a significantly larger area under the curve (AUC) than MMSE (0.96 vs 0.88, P = .03) and was equivalent to MoCA in detecting CI (0.96 vs 0.95, P = .80). At the optimal cutoff points, the TYM (<38) was significantly more sensitive than the MMSE (<24) and MoCA (<20; P < .001). The RBANS had an AUC equivalent to the RBANS supplemented with CTT and mBNT (0.92 vs 0.86, P = .22) in detecting CI. The RBANS supplemented with CTT and mBNT was more sensitive than RBANS alone in detecting CI (sensitivity: 0.98 vs 0.93, P = .016) among patients screened negative using TYM. Conclusion: The self-administered TYM is superior to MMSE and equivalent to MoCA in detecting CI and could be implemented routinely. The RBANS supplemented with CTT and mBNT is more sensitive in detecting CI than RBANS alone therefore could be used for diagnostic purposes.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 0.001 |
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".