Affective and emotional dysregulation as pre-dementia risk markers: exploring the mild behavioral impairment symptoms of depression, anxiety, irritability, and euphoria
Bibliographic record
Abstract
BACKGROUND: Affective and emotional symptoms such as depression, anxiety, euphoria, and irritability are common neuropsychiatric symptoms (NPS) in pre-dementia and cognitively normal older adults. They comprise a domain of Mild Behavioral Impairment (MBI), which describes their emergence in later life as an at-risk state for cognitive decline and dementia, and as a potential manifestation of prodromal dementia. This selective scoping review explores the epidemiology and neurobiological links between affective and emotional symptoms, and incident cognitive decline, focusing on recent literature in this expanding field of research. METHODS: Existing literature in prodromal and dementia states was reviewed, focusing on epidemiology, and neurobiology. Search terms included: "mild cognitive impairment," "dementia," "prodromal dementia," "preclinical dementia," "Alzheimer's," "depression," "dysphoria," "mania," "euphoria," "bipolar disorder," and "irritability." RESULTS: Affective and emotional dysregulation are common in preclinical and prodromal dementia syndromes, often being harbingers of neurodegenerative change and progressive cognitive decline. Nosological constraints in distinguishing between pre-existing psychiatric symptomatology and later life acquired NPS limit historical data utility, but emerging research emphasizes the importance of addressing time frames between symptom onset and cognitive decline, and age of symptom onset. CONCLUSION: Affective symptoms are of prognostic utility, but interventions to prevent dementia syndromes are limited. Trials need to assess interventions targeting known dementia pathology, toward novel pathology, as well as using psychiatric medications. Research focusing explicitly on later life onset symptomatology will improve our understanding of the neurobiology of NPS and neurodegeneration, enrich the study sample, and inform observational and clinical trial design for prevention and treatment strategies.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".