<scp>Post‐traumatic</scp> stress disorder mistaken for behavioural and psychological symptoms of dementia: case series and recommendations of care
Bibliographic record
Abstract
In late life, traumas may act cumulatively to exacerbate vulnerability to post-traumatic stress disorder (PTSD). PTSD is also a risk factor for cognitive decline. Major neurocognitive disorder (MND) can be associated with worsening of already controlled PTSD symptoms, late-life resurgence or de novo emergence. Misidentifying PTSD symptoms in MND can have negative consequences for the patient and families. We review the literature pertaining to PTSD and dementia and describe five cases referred for consultation in geriatric psychiatry initially for behavioural and psychological symptoms of dementia (BPSD), which were eventually diagnosed and treated as PTSD in MND subjects. We propose that certain PTSD symptoms in patients with MND are misinterpreted as BPSD and therefore, not properly addressed. For example, flashbacks could be interpreted as hallucinations, hypervigilance as paranoia, nightmares as sleep disturbances, and hyperreactivity as agitation/aggression. We suggest that better identification of PTSD symptoms in MND is needed. We propose specific recommendations for care, namely: clarifying diagnosis by distinguishing PTSD symptoms coexisting with different types of dementia from a specific dementia symptom (BPSD), gathering a detailed history of the trauma in order to personalise non-pharmacological interventions, adapting psychotherapeutic strategies to patients with dementia, using selective serotonin reuptake inhibitors as first-line treatment and avoiding antipsychotics and benzodiazepines. Proper identification of PTSD symptoms in patients with MND is essential and allows a more tailored and efficient treatment, with decrease in inappropriate use of physical and chemical restraints.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.008 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".