1271-P: Longitudinal Predictors of Cognitive Impairment in Older Adults with Type 2 Diabetes—A Systematic Review
Bibliographic record
Abstract
Introduction and Objective: Older adults with diabetes are at an increased risk of cognitive impairment (CI). Those with diabetes may experience distinct biological, psychological, interpersonal, and behavioral risk factors for CI compared to those without diabetes. However, current preventive strategies often do not address disease-specific factors, and their effectiveness remains uncertain. This review aimed to summarize the longitudinal predictors of CI in older adults with type 2 diabetes (T2DM) and to identify those at higher risk. Methods: We systematically searched PubMed, CINAHL, PsycINFO, and Cochrane Library in December 2024. Two reviewers screened records for eligibility, extracted data, and assessed risk of bias using the Newcastle-Ottawa Scale. Findings were synthesized narratively. Results: A total of 35 longitudinal studies were included in the synthesis. Sample sizes ranged from 55 to 2,032,689, and mean follow-up periods ranged from 2.5 to 14.7 years, when reported. In total, 25 biological, 7 behavioral, and 1 interpersonal predictor were identified. Biological predictors included blood/urine biomarkers (14), physical biomarkers (3), overall physical conditions (3), diabetes-specific conditions/status (3), and one genetic biomarker. Behavioral predictors included smoking, alcohol use, diet/nutrients, physical activity, and sleep. Social contact was the sole interpersonal predictor. No psychological predictors were reported. Except for the genetic biomarker, most predictors were modifiable. Conclusion: Given the absence of a cure for CI, identifying those at heightened risk and providing targeted preventive care are critical. Diabetes-specific factors should be integrated into the design of preventive strategies for older adults with T2DM to mitigate the risk of CI. Disclosure M. Kim: None. B. Kim: None. Funding Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (RS-2023-00250911)
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.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".