Effect of Linagliptin on Cognitive Performance in Patients With Type 2 Diabetes and Cardiorenal Comorbidities: The CARMELINA Randomized Trial
Bibliographic record
Abstract
OBJECTIVE: Type 2 diabetes is associated with cognitive dysfunction and an increased dementia risk, particularly in individuals with concomitant cardiovascular and/or kidney disease. Incretin therapies may modulate this risk via glycemic and nonglycemic pathways. We explored if the dipeptidyl peptidase 4 inhibitor linagliptin could prevent cognitive decline in people with type 2 diabetes with cardiorenal disease. RESEARCH DESIGN AND METHODS: The CArdiovascular and Renal Microvascular outcomE study with LINAgliptin (CARMELINA)-COG substudy was an integral part of CARMELINA (NCT01897532) that randomized participants with cardiorenal disease to linagliptin 5 mg or placebo once daily (1:1), in addition to standard of care. The primary cognitive outcome was the occurrence of accelerated cognitive decline at the end of treatment, defined as a regression-based index score ≤16th percentile on the Mini-Mental State Examination (MMSE) or a composite measure of attention and executive functioning and analyzed in participants with a baseline MMSE ≥24. Effects across subgroups by baseline factors, as well as absolute cognitive changes, were also assessed. RESULTS: , 7.8 ± 0.9% [61.4 ± 10.1 mmol/mol]). Over a median treatment duration of 2.5 years, accelerated cognitive decline occurred in 28.4% (linagliptin) vs. 29.3% (placebo) (odds ratio 0.96 [95% CI 0.77, 1.19]). Consistent effects were observed across subgroups by baseline characteristics. Absolute cognitive performance changes were also similar between treatment groups. CONCLUSIONS: In a large international cardiovascular outcome trial in people with type 2 diabetes and cardiorenal disease, linagliptin did not modulate cognitive decline over 2.5 years.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".