Cognitive performance of older adults in a specialized diabetes clinic
Bibliographic record
Abstract
BACKGROUND: Diabetes mellitus is a risk factor for cognitive changes, but assessment for cognitive disorders in this population is performed infrequently. The present study examined the frequency of cognitive disorders and patterns of deficit in patients enrolled in a specialized clinic for diabetes. METHODS: A cross-sectional study was conducted to assess cognition in Mount Sinai Diabetes Center patients. Thirty eligible subjects aged ≥50 years were assessed and compared with non-diabetic cognitively normal control subjects, as well as non-diabetic subjects with mild cognitive impairment (MCI). The main outcome(s) and measure(s) were obtained through cognitive assessment and diagnosis using the Alzheimer's Disease Centers' uniform data set. RESULTS: Forty percent of subjects were newly diagnosed with a cognitive disorder: 10% were diagnosed with dementia and 30% with MCI. Diabetic subjects performed worse on the Mini-Mental State Examination (27.2 vs 28.4; P = 0.0132), list generation (9.5 vs 12.2; P = 0.0190), Trail Making Test, Parts A (70.1 vs 43.0; P < 0.0001) and B (197.2 vs 123.6; P < 0.0001), and the Digit Symbol test (12.7 vs 40.1; P < 0.0001) than cognitively normal individuals. Compared with subjects with MCI (amnestic type), diabetic subjects performed better on tasks of immediate and delayed recall (11.2 vs 7.3 [P = 0.0048] and 8.4 vs. 4.1 [P = 0.0003], respectively). CONCLUSIONS: Undiagnosed cognitive disorders are common and underappreciated in patients being treated in a specialized diabetes clinic. It may be important to make cognitive assessment a standard part of patient assessments.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 teacher head, 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".