Usefulness of the Montreal Cognitive Assessment in Older Adults With Type 1 Diabetes
Why this work is in the frame
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Bibliographic record
Abstract
Objective: Older adults with type 1 diabetes are at high risk for cognitive impairment, yet the usefulness of common cognitive screening instruments has not been evaluated in this population. Methods: A total of 201 adults ≥60 years of age with type 1 diabetes completed a battery of neuropsychological measures and the Montreal Cognitive Assessment (MoCA). Receiver operating characteristic (ROC) curves and Youden indices were used to evaluate overall screening test performance and to select an optimal MoCA cutoff score for detecting low cognitive performance, as defined as two or more neuropsychological test performances ≥1.5 SD below demographically corrected normative data. Results: < 0.001). The publisher-recommended cutoff score of <26 resulted in sensitivity of 60.4% and specificity of 71.4%, whereas a cutoff score of <27 resulted in sensitivity of 75.0% and specificity of 61.0%. The Youden indices for these cutoff scores were 0.318 and 0.360, respectively. Minimally acceptable sensitivity (i.e., >0.80) was obtained when using a cutoff score of <28, whereas >0.80 specificity was obtained with a cutoff score of <25. Conclusions: The MoCA has modest overall performance (AUC 0.745) as a cognitive screening instrument in older adults with type 1 diabetes. The standard cutoff score of <26/30 may not adequately detect individuals with neuropsychological testing-defined abnormal cognition. The optimal MoCA cutoff score (based on the Youden index) was <27/30. A score of <28 resulted in acceptable sensitivity but was accompanied by low specificity (42%). Future studies with a more diverse population are needed to confirm these findings.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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 it