On the association between apathy and deficits of social cognition and executive functions in Huntington’s disease
Bibliographic record
Abstract
OBJECTIVE: To investigate if executive and social cognitive dysfunction was associated with apathy in a large cohort of Huntington's disease gene expansion carriers. METHOD: Eighty premanifest and motor-manifest Huntington's disease gene expansion carriers (Mini-Mental State Examination score ≥ 24 and Montreal Cognitive Assessment score ≥ 19) and thirty-two controls were examined with the Lille Apathy Rating Scale (LARS), a tailored and quantitative measure of apathy, and a comprehensive cognitive battery on executive functions and social cognition (emotion recognition, theory of mind and sarcasm detection), as well as general correlates like demographic variables, and neuropsychiatric and cognitive screening tests. RESULTS: The motor-manifest Huntington's disease gene expansion carriers had significantly different scores on most measures of social cognition and executive functions, compared to premanifest and control participants. Apathy was significantly correlated with most executive test scores, but the Emotion Hexagon was the only social cognitive test score significantly correlated with apathy. We found that the motor score and the depression score were the only significant predictors of the apathy score, when the social cognitive and executive tests with the strongest association with the global LARS score were entered into a multiple stepwise regression model. No cognitive test score could significantly predict apathy. The model explained 21 % of the total variance. CONCLUSION: Despite being significantly correlated with apathy neuropsychological variables did not have a significant impact on apathy when variables as depression and motor symptoms were taken into account. Apathy should be considered an independent symptom of Huntington's disease that requires specific examination.
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 | 0.002 |
| 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 | 0.000 | 0.000 |
| 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".