[18F]FDDNP PET binding predicts change in executive function in a pilot clinical trial of geriatric depression
Bibliographic record
Abstract
OBJECTIVES: Geriatric depression often presents with memory and cognitive complaints that are associated with increased risk for Alzheimer's disease (AD). In a parent clinical trial of escitalopram combined with memantine or placebo for geriatric depression and subjective memory complaints, we found that memantine improved executive function and delayed recall performance at 12 months (NCT01902004). In this report, we used positron emission tomography (PET) to assess the relationship between in-vivo amyloid and tau brain biomarkers and clinical and cognitive treatment response. DESIGN: In a randomized double-blind placebo-controlled trial, we measured 2-(1-{6-[(2-[F18]fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene) malononitrile ([18F]FDDNP) binding at baseline and assessed mood and cognitive performance at baseline, posttreatment (6 months), and naturalistic follow-up (12 months). PARTICIPANTS: Twenty-two older adults with major depressive disorder and subjective memory complaints completed PET scans and were included in this report. RESULTS: Across both treatment groups, higher frontal lobe [18F]FDDNP binding at baseline was associated with improvement in executive function at 6 months (corrected p = .045). This effect was no longer significant at 12 months (corrected p = .12). There was no association of regional [18F]FDDNP binding with change in mood symptoms (corrected p = .2). CONCLUSIONS: [18F]FDDNP binding may predict cognitive response to antidepressant treatment. Larger trials are required to further test the value of [18F]FDDNP binding as a biomarker for cognitive improvement with antidepressant treatment in geriatric depression.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".