3A COMPARISON OF THE AMTS VS MOCA IN OLDER PATIENTS ADMITTED TO ACUTE MEDICINE
Bibliographic record
Abstract
Introduction: The 10-point Abbreviated Mental Test Score (AMTS) is feasible and valid in the acute hospital setting but may be insensitive to milder cognitive deficits. The Montreal Cognitive Assessment (MoCA), is a more detailed 30-point screening assessment that has been extensively validated but there are few data from the hospital population. We therefore compared the performance of the AMTS vs MoCA in older patients admitted to acute medicine. Methods: The Oxford University Hospitals NHS Trust (OUHFT) cognitive screen including the AMTS was administered to patients aged ≥75 admitted to acute general medicine together with the MoCA in those still hospitalised at >72 hours. Numbers with low AMTS (<9) and low MoCA (<26) were determined together with MoCA subtest performance. Results: Among 183 patients, mean/standard deviation (sd) age = 84.5/7.2 years, AMTS was skewed towards normal values (mean/sd AMTS = 7.0/2.6, range 0–10) whereas MoCA scores were normally distributed (mean/sd MoCA = 16.1/6.2, range 2–28). Although AMTS and MoCA were strongly correlated (p < 0.0001), only 10 patients (5%) had normal MoCA compared to 72 (38%) with normal AMTS. The majority of patients with normal AMTS had low MoCA score (62/72 (86%)) whereas none of the 10 patients with normal MoCA had low AMTS. MoCA subtest performance (% correct) was worst for delayed recall (16%), verbal fluency (28%) and visuoexecutive function (45%) and best for naming (80%). MoCA scores were significantly lower (mean/sd MoCA = 12.8/5.4) in low AMTS vs normal AMTS (mean/sd MoCA = 20.8/3.5, p < 0.0001) groups with all MoCA subtests showing discriminant value. Conclusion: The AMTS has a ceiling effect such that the majority of patients with normal AMTS have abnormal MoCA with deficits across a wide range of cognitive domains. Clinicians should be aware that a “normal” AMTS does not exclude cognitive impairment and that more detailed assessment may be required.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".