Posttraumatic stress symptom severity predicts cognitive decline beyond the effect of Alzheimer’s disease biomarkers in Veterans
Bibliographic record
Abstract
Chronic stress is a risk factor for dementia but whether it explains unique variance in cognitive decline in older adults above Alzheimer's disease (AD) biomarkers is unknown. In a preclinical cohort of Vietnam Veterans, we examined the relationship between posttraumatic stress disorder (PTSD) symptom severity, AD biomarkers of beta-amyloid (Aβ) and tau, and change in cognitive performance on two widely-used screeners, the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). Analyses indicated that PTSD symptom severity was associated with a greater decline on the MMSE (p < 0.04) and MoCA (p < 0.024) after adjusting for biomarkers of AD, notably on the attention scale of the MoCA and the memory index of the MMSE. These analyses survived multiple comparison corrections. Taken together, PTSD symptom severity is associated with accelerated cognitive decline. Treating PTSD should be considered instrumental to maintaining cognitive function as adults age.
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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) | 0.000 | 0.000 |
| 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 | 0.000 | 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".