Veterans Affairs Saint Louis University Mental Status Examination Compared with the Montreal Cognitive Assessment and the Short Test of Mental Status
Bibliographic record
Abstract
OBJECTIVES: To compare the ability of the Veterans Affairs Saint Louis University Mental Status (SLUMS) examination to detect mild cognitive impairment (MCI) and dementia according to the Clinical Dementia Rating Scale (CDR) with that of two other well-known screening instruments, the Montreal Cognitive Assessment (MoCA) and the Short Test of Mental Status (STMS). DESIGN: Cross-sectional validation study. SETTING: Saint Louis Veterans Affairs Medical Center Geriatric Research Education and Clinical Center. PARTICIPANTS: Veterans aged 60 and older (median 78.5) with a high school education or more (n = 136). MEASUREMENTS: Participants were administered the SLUMS examination, the MoCA, and the STMS in random order. A blinded test administrator administered the CDR in a separate session. Receiver operating characteristic (ROC) curves were used to assess the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the SLUMS examination, the MoCA, and the STMS for MCI, dementia, and MCI or dementia. ROC contrasts were used to statistically compare the area under the ROC curve (AUC) for the screening tests' ability to detect cognitive dysfunction according to the CDR. RESULTS: ROC contrasts demonstrated that the AUCs for detecting MCI (SLUMS examination 0.74, MoCA 0.77, STMS 0.77), dementia (SLUMS examination 0.98, MoCA 0.96, STMS 0.97), and MCI or dementia (SLUMS examination 0.82, MoCA 0.83, STMS 0.84) were equivalent. Sensitivity, specificity, PPV, and NPV were similar across measures of MCI, dementia, and MCI or dementia according to the CDR. CONCLUSION: The SLUMS examination has validity similar to that of the MoCA and STMS for the detection of MCI, dementia, and MCI or dementia according to the CDR.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".