A-015 Posttraumatic Stress Disorder Symptoms are Associated with Reduced Performance on the MoCA among Vietnam Veterans
Bibliographic record
Abstract
Abstract Objective To examine cross-sectional associations between posttraumatic stress disorder (PTSD) symptom severity, number of stressors experienced, and cognitive outcomes in Vietnam War veterans. Methods 366 adults between the ages of 60–85 years old completed a Vietnam Veterans Alzheimer’s Disease Neuroimaging Initiative Project (ADNI-DoD) visit consisting of a clinical interview and neuropsychological assessment. Number of stressful experiences were measured with the Life Stressor Checklist-Revised (LSC-R). Severity scores were assessed via the current Clinician-Administered PTSD Scale (CAPS). Correlations were conducted between selected measures of stress and age, years of education, sex, ethnicity, and race. Demographic variables with significant associations with stress were included as covariates in the hierarchical regressions. Hierarchical linear regressions were conducted to examine the effect of CAPS and LSC-R on baseline Montreal Cognitive Assessment (MoCA) scores. Results Higher CAPS scores (indicating higher PTSD severity) were associated with worse cognitive outcomes on the MoCA [ΔF(1,269) = 15.058, p < 0.001, R2 = 0.116]. By contrast, number of stressful experiences was not associated with cognitive outcomes. Follow up analyses indicated that CAPS severity scores were significantly associated with the memory index and the attention index of the MoCA. Conclusions In a sample of older veterans, PTSD symptom severity was associated with worse performance on the MoCA. Moreover, further analyses indicated that results within the memory and attention domains are driving these results. As such, treating PTSD symptoms may be helpful in 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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".