Neuropsychiatric and Cognitive Subtypes among Community-Dwelling Older Persons and the Association with DSM-5 Mild Neurocognitive Disorder: Latent Class Analysis
Bibliographic record
Abstract
BACKGROUND: Neuropsychiatric symptoms (NPS) have been shown to increase the risk of neurocognitive disorders (NCD), leading to the recently-published criteria of mild behavioral impairment (MBI) to identify pre-dementia using NPS alone. However, MBI drew concerns about over-diagnosing subclinical psychiatric disorders. OBJECTIVE: We hypothesized that the specificity of NPS in predicting NCD may be improved by considering NPS together with various domains of cognitive deficits. We tested this hypothesis by identifying subtypes based on the combination of NPS and cognitive deficits among community-dwelling older persons, and evaluating how the identified subtypes were associated with mild NCD. METHODS: Our participants were from a community-based cohort study. They completed assessments such as Geriatric Depression Scale (GDS), Geriatric Anxiety Inventory (GAI), and Montreal Cognitive Assessment (MoCA). Those with possible cognitive impairment underwent further evaluations for mild NCD. Latent class analysis was conducted using GDS, GAI, and MoCA domains. Logistic regression was performed to investigate the association between the latent-classes and mild NCD. RESULTS: We included 825 participants, and identified four distinct subtypes: Subtype 1 (no NPS or cognitive deficits), Subtype 2 (NPS alone), Subtype 3 (cognitive deficits alone), and Subtype 4 (both NPS and cognitive deficits). Subtype 1 and 2 had low risk of prevalent mild NCD (OR 0.92- 1.00), while Subtype 3 conferred a moderate risk (OR 4.47- 4.85) and Subtype 4 had the highest risk (OR 7.95- 8.63). CONCLUSION: We demonstrated the benefits of combining NPS and cognitive deficits to predict those at highest risk of prevalent mild NCD. Our findings highlighted the relevance of subclinical psychiatric symptoms in predicting NCD, and indirectly supported the need for longer durations of NPS to improve its specificity.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".