Prevalence of Late Onset Stress Symptomatology (LOSS) in geriatric combat veterans and its relation with dementia: A Pilot Study
Bibliographic record
Abstract
Introduction Late onset stress symptomatology (LOSS) is a relatively new concept in combat veterans, which includes repeated but not intrusive thoughts about combat-related experiences, irritability, or nightmares that do not cause impairment of daily functioning. Objectives The objectives of this study were to identify the LOSS phenomenon in geriatric combat veterans and to establish a correlation between LOSS and cognitive deficit ± major stressors. Methods The electronic database was searched for the last 2 years from starting the study with the hypothesis that the LOSS phenomenon has been diagnosed with sleep, anxiety, trauma-related, or impulse control related disorders. Records were examined for trauma-related symptoms, excluding major symptoms of trauma-related stressors. The veterans were assessed objectively using LOSS, PCL-5 (PTSD checklist for DSM-5), social readjustment rating scales, and MOCA (Montreal Cognitive Assessment scale) for cognitive screening. Results We reviewed 1329 patient records and identified 35 potential LOSS subjects. Four veterans were diagnosed with PTSD not otherwise specified, 2 with anxiety disorder unspecified, and 1 veteran with nightmare disorder. The majority (85%) of the veterans scored >40 in PCL-5, and only one veteran fulfilled the criteria for LOSS, who scored 67 on the LOSS scale. All the veterans scored ≤25 on MOCA with a significant deficit in recent recall. Conclusions Our study shows new onset stress-related symptoms are strongly associated with significant cognitive deficits and higher individual stress levels. The onset of PTSD symptoms in older combat veterans might have been correlated with the onset of cognitive deficits, as suggested by several other studies. Disclosure No significant relationships.
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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 | 0.002 | 0.001 |
| 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) | 0.001 | 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".