Association of Depression With Accelerated Cognitive Decline Among Patients With Type 2 Diabetes in the ACCORD-MIND Trial
Bibliographic record
Abstract
IMPORTANCE: Depression has been identified as a risk factor for dementia among patients with type 2 diabetes mellitus but the cognitive domains and patient groups most affected have not been identified. OBJECTIVE: To determine whether comorbid depression in patients with type 2 diabetes accelerates cognitive decline. DESIGN: A 40-month cohort study of participants in the Action to Control Cardiovascular Risk in Diabetes-Memory in Diabetes (ACCORD-MIND) trial. SETTING: Fifty-two clinics organized into 6 clinical networks across the United States and Canada. PARTICIPANTS: Two thousand nine hundred seventy-seven participants with type 2 diabetes at high risk for cardiovascular events. INTERVENTION: The Digit Symbol Substitution Test, Rey Auditory Verbal Learning Test, and the modified Stroop test were used to assess cognition. The 9-item Patient Health Questionnaire was used to assess depression. MAIN OUTCOMES AND MEASURES: Mixed-effects statistical models were used to analyze cognitive test outcomes incorporating depression as a time-dependent covariate. RESULTS: Participants with scores indicative of depression (9-item Patient Health Questionnaire, ≥10) showed greater cognitive decline during 40-month follow-up on all tests, with the following differences in estimated least squares means: Digit Symbol Substitution Test, 0.72 (95% CI, 0.25 to 1.19; P = .003), Rey Auditory Verbal Learning Test, 0.18 (95% CI, 0.07 to 0.29; P = .001), and Stroop interference, -1.06 (95% CI, -1.93 to -0.18; P = .02). This effect of depression on risk of cognitive decline did not differ according to previous cardiovascular disease; baseline cognition or age; or intensive vs standard glucose-lowering treatment, blood pressure treatment, lipid treatment, or insulin treatment. Addition of demographic and clinical covariates to models did not significantly change the cognitive decline associated with depression. CONCLUSIONS AND RELEVANCE: Depression in patients with type 2 diabetes was associated with greater cognitive decline in all domains, across all treatment arms, and in all participant subgroups assessed. Future randomized trials will be necessary to determine if depression treatment can lower the risk of cognitive decline in patients with diabetes.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".