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Record W4393114796 · doi:10.1007/s13300-024-01549-y

Validity of Montreal Cognitive Assessment to Detect Cognitive Impairment in Individuals with Type 2 Diabetes

2024· article· en· W4393114796 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDiabetes Therapy · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersIndian Council of Medical Research
KeywordsMontreal Cognitive AssessmentMedicineCognitive impairmentType 2 diabetesDiabetes mellitusCognitionGerontologyPsychiatryEndocrinology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.023
GPT teacher head0.341
Teacher spread0.319 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it