Apathy as a treatment target in neurocognitive disorders: Clinical trial implications
Bibliographic record
Abstract
Abstract Background Apathy is the most prevalent, stable and persistent neuropsychiatric symptom observed across the neurocognitive disorders spectrum and is linked to poorer disease outcome, reduced daily functioning and higher levels of caregiver distress, and an increased risk of mortality. Recent advances in understanding of phenomenology, neurobiology and intervention trials highlight an increased interest in and recognition of apathy as an important target for clinical intervention. We therefore conducted a comprehensive review and critical evaluation of recent advances to determine evidence‐based suggestions for future trial designs. Method A critical review of latest research on apathy as a treatment target in pre‐dementia and dementia populations by the Alzheimer’s Association International Society to Advance Alzheimer’s Research and Treatment (ISTAART) Neuropsychiatric Syndromes Professional Interest Area (NPS‐PIA) Apathy Workgroup. This review focused on 4 key areas: 1) mechanisms and biomarkers; 2) assessment; 3) treatment and intervention efficacy; and 4) pre‐dementia states. Result Considerable progress has been made in understanding apathy as a treatment target and appreciating pharmacological and non‐pharmacological apathy treatment interventions. Areas of the literature requiring greater investigation include: diagnostic procedures, symptom measurement, understanding the biological mechanisms and biomarkers of apathy, and a carefully considered and well‐formed approach to the development of treatment strategies. Conclusion We have made much progress in better understanding the role of apathy in affecting the impact and course of neurocognitive disorders and are starting to see some successes in targeting new treatments. To advance the recognition of apathy as a treatment target for clinical trials, it is essential that a better understanding of the subdomains and biological mechanisms of apathy are achieved. We propose the utility of a comprehensive multi‐national longitudinal observational study of neuropsychiatric symptoms in which the study of apathy is incorporated.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".