Recommendations for management and future investigation of psychosis in neurodegenerative disease: Findings from the International Psychogeriatric Association (IPA) working group
Bibliographic record
Abstract
INTRODUCTION: Psychosis is frequently observed in patients with neurodegenerative disease and may precede onset of cognitive symptoms. Additionally, the presence of psychosis in neurodegenerative disease is often associated with adverse effects including increased progression of cognitive decline and conversion to dementia, increased caregiver burden, and increased rates of placement in long-term care. Moreover, existing pharmacological treatments, which consist principally of off-label antipsychotic medications, may be associated with increased risk of harm, making management of symptoms challenging. OBJECTIVE: We review recent advances in the field of psychosis in neurodegenerative disease, including advances in clinical criteria, biomarkers (neuroimaging, pathology, and genomic and epigenomics), and treatments. METHOD: Under the direction of the International Psychogeriatric Association (IPA), a task force comprised of experts in the field of psychosis in neurodegenerative disease was convened. An in-person meeting was organized in September 2024, coincident with the annual IPA Congress. The task force undertook a review of the literature in the areas of clinical care, biomarkers, and treatment, from which key recommendations for the management and future investigation of psychosis in neurodegenerative disease were derived. RESULTS: It was concluded that psychosis in neurodegenerative disease has a characteristic phenomenology that despite sharing some features with schizophrenia spectrum psychotic disorders, may differ in other clinically meaningful aspects. Etiopathogenesis based on biomarker, genomic, and treatment studies may differ to some extent among neurodegenerative diseases. There is emerging evidence supporting the use of prescriptive non-pharmacological (WHELD intervention) and novel pharmacological (pimavanserin, muscarinic agonists) approaches in the treatment of psychosis in neurodegenerative disease. CONCLUSION: Future directions include the need for the implementation of evidence-based nonpharmacological treatments consistent with the aims of precision medicine, further investigation into novel pharmacological agents, mapping specific psychotic symptoms to specific biomarkers, and further exploration of the link between psychosis in neurodegenerative disease and other late-life psychoses.
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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 | 0.043 | 0.085 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.019 | 0.019 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".