1367-P: Cognitive Assessment in Type 2 Diabetes—A Pilot Study in an Outpatient Clinic
Bibliographic record
Abstract
Aim: Type 2 diabetes (T2D) is associated with an increased risk of cognitive decline which may impact diabetes self-care and outcomes. Assessment of cognitive function is not routine practice. The primary objective was to assess cognitive function in outpatients >55 years with T2D. Method: People with T2D (> 55 years) attending a tertiary hospital diabetes outpatient clinic with no known cognitive impairment and sufficient English language skills were recruited. The Montreal Cognitive Assessment and Problem Areas in Diabetes questionnaires were completed with a trained investigator. Routine demographic and clinical data were obtained from healthcare records. Analysis was descriptive and results expressed as mean ± standard deviation. Institutional ethics approval was obtained. Results: Forty patients were enrolled, age 71.3 ± 8.7 years, 75% male, diabetes duration was 15.4 ±8.7 years and current HbA1c 7.7% ± 1.2%. The number of medications prescribed was 8.2 ± 3.7. The PAID score was 14.2 ± 13.3. In 27/40 (67.5%) patients the MOCA score was <26/30 (23.6 ± 2.8) indicating cognitive impairment. The number of medications prescribed to this group was 8.4 ± 3.7. High risk medicines were prescribed to 23/27 (85%) of this cohort of patients. Conclusion: Cognitive screening highlighted the prevalence of impairment in this outpatient clinic population (67.5%). Inclusion of routine cognitive screening can identify people who may benefit from additional diabetes management support and appropriate modifications to treatment regimens. This data will inform plans to implement routine screening in accordance with professional guidelines and screening principles. Disclosure J. Ludington: None. R. Chen: Speaker's Bureau; Abbott Diagnostics, AstraZeneca, Boehringer-Ingelheim. Advisory Panel; Eli Lilly and Company. Speaker's Bureau; Eli Lilly and Company. Advisory Panel; Novo Nordisk. Speaker's Bureau; Novo Nordisk. D. Gnjidic: None.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".