Executive impairment is associated with unawareness of neuropsychiatric symptoms in premanifest and early Huntington’s disease.
Bibliographic record
Abstract
OBJECTIVE: Unawareness of neuropsychiatric symptoms appears to be common in Huntington's disease (HD), but the clinical correlates of unawareness are unclear. Identifying predictors of unawareness is important for improving diagnosis of neuropsychiatric symptoms, and cognitive impairment, specifically executive impairment, may be a potential important predictor of unawareness. The authors examined whether unawareness of neuropsychiatric symptoms is more common in early HD compared to premanifest HD, and whether executive task performance was associated with awareness, independent of demographic, motor or mood variables. METHOD: One hundred thirty-two gene-positive participants (60 premanifest and 72 early diagnosed) from the multicenter TRACK-HD study were included. Participants and their informants completed self and informant versions of the Frontal Systems Behavior Scale, which measures executive dysfunction, apathy, and disinhibition symptoms. Awareness was measured as the discrepancy between self- and informant-reports across premanifest and early HD groups. Participants' executive task performance was then assessed as a predictor of unawareness across the whole group. RESULTS: Premanifest participants reported higher levels of executive dysfunction, apathy and disinhibition than their informants, whereas early HD participants reported less executive dysfunction and apathy than their informants, indicating that unawareness is more common after diagnosis. Impaired executive task performance was related to unawareness of executive dysfunction and apathy, independent of demographic, motor and mood variables. CONCLUSIONS: Executive impairment is a useful early predictor of unawareness of neuropsychiatric symptoms in HD. Clinicians should closely monitor HD patients with executive impairment for unawareness, and consider this when assessing neuropsychiatric symptoms in HD and providing education to patients and families. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".