Validity of Montreal Cognitive Assessment to Detect Cognitive Impairment in Individuals with Type 2 Diabetes
Bibliographic record
Abstract
Guidelines recommend screening older people (> 60–65 years) with type 2 diabetes (T2D) for cognitive impairment, as it has implications in the management of diabetes. The Montreal Cognitive Assessment (MoCA) is a sensitive test for the detection of mild cognitive impairment (MCI) in the general population, but its validity in T2D has not been established. We administered MoCA to patients with T2D (age ≥ 60 years) and controls (no T2D), along with a culturally validated neuropsychological battery and functional activity questionnaire. MCI was defined as performance in one or more cognitive domains ≥ 1.0 SD below the control group (on two tests representing a cognitive domain), with preserved functional activities. The discriminant validity of MoCA for the diagnosis of MCI at different cut-offs was ascertained. We enrolled 267 patients with T2D and 120 controls; 39% of the participants with T2D met the diagnostic criteria for MCI on detailed neuropsychological testing. At the recommended cut-off on MoCA (< 26), the sensitivity (94.2%) was high, but the specificity was quite low (29.5%). The cut-off score of < 23 showed an optimal trade-off between sensitivity (69.2%), specificity (71.8%), and diagnostic accuracy (70.8%). The cut-off of < 21 exhibited the highest diagnostic accuracy (74.9%) with an excellent specificity (91.4%), a good positive and negative predictive value (78.5% and 73.7%, respectively). The recommended screening cut-off point on MoCA of < 26 has a suboptimal specificity and may increase the referral burden in memory clinics. A lower cut-off of < 21 on MoCA maximizes the diagnostic accuracy. Interactive Visual Abstract available for this article. Type 2 diabetes (T2D) is a risk factor for cognitive dysfunction which potentially impacts diabetes self-management skills. Guidelines recommend screening older adults with diabetes for early detection of cognitive impairment. For screening cognitive impairment in busy endocrine clinics, we need a test that is easy and rapid to administer, sensitive enough to pick the cognitive deficits of T2D and at the same time gives less false-positive outcomes. The Montreal Cognitive Assessment (MoCA) scale is a widely available cognitive screening tool, but there are no studies evaluating its discriminant properties in people with diabetes. We evaluated the performance metrics of MoCA in this population. We found mild cognitive impairment in four out of ten participants with T2D at or above 60 years of age. At the recommended cut-off on MoCA (< 26), the sensitivity was high, but the specificity quite low. We found better diagnostic accuracy at lower cut-offs (20/21), with high specificity but a lower sensitivity. At this cut-off, approximately one out of five people screened using MoCA would require detailed neuropsychological testing, and four out of five who undergo detailed evaluation would have true cognitive impairment.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 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 | 0.000 |
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".