Relationships between memory decline and the use of metformin or DPP4 inhibitors in people with type 2 diabetes with normal cognition or Alzheimer's disease, and the role <i>APOE</i> carrier status
Bibliographic record
Abstract
INTRODUCTION: Few studies have examined memory decline among patients with type 2 diabetes using different oral hypoglycemic drugs. METHODS: Participants with normal cognition (NC) or Alzheimer's disease (AD) dementia using a hypoglycemic medication (2005 to 2019) were identified from the National Alzheimer's Coordinating Center database. Delayed memory was assessed using the Wechsler Memory Scale Revised-Logical Memory test. Associations between oral drug classes and memory over time were examined using mixed-effects models with inverse probability treatment weights. RESULTS: In NC (n = 1192), metformin use was associated with better memory performance over time, whereas in AD (n = 807), dipeptidyl peptidase-4 (DPP4) inhibitor use was associated with a slower rate of memory decline. Interaction effects suggested greater benefit associated with DPP4 inhibitor use among APOE ε4 carriers. DISCUSSION: Associations between different oral hypoglycemic drugs and memory change were not consistent between cognitively normal elderly and those with AD dementia. APOE ε4 genotype modified some relationships.
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".