F066 Clinical and epidemiological aspects of neuropsychiatric features in patients with Huntington disease in Chile
Bibliographic record
Abstract
Background There is limited data in Chile regarding motor and non-motor features of patients with Huntington’s disease (HD). However, it is well-established that neuropsychiatric events are present throughout the evolution of HD. Objective To describe the prevalence of motor and neuropsychiatric symptoms in HD patients seen at CETRAM, Santiago, Chile. Methods This is a retrospective, descriptive study of patients with HD seen at CETRAM between 2014 and 2023. We investigated the patients‘ family background, genetic tests (either personal or first-degree relative), and neuropsychiatric features. Symptoms correlated with their age of onset were recorded. The repeat length (RL) of the CAG trinucleotide expansion mutation in the HTT gene was divided into three groups: 36–42, 43–48, and 49 or above. We explored the correlation between symptoms and factors such as sex, RL, age at onset of symptoms, and years of diagnosis. Results The study included 70 patients with an average age of 49.44 years (SD=13.69). 62.9% were women and 37.1% were men. Maternal and paternal inheritance was identified in 40% and 48.57% of cases, respectively. 2.86% had no family history, and 8.57% were still unknown. According to the reported information, a medical history of neuropsychiatric characteristics included depression (68.6%), irritability (77.1%), violent behavior (47.1%), apathy (67.1%), obsessive behavior (75.7%), psychosis (24.3%), cognitive impairment (12.9%), and previous suicidal ideation or attempts (12.9%). Motor symptoms were present in 88.6% of patients. No statistically significant association (SSA) was found between gender and symptoms. However, there was an SSA between violent behavior and RL (P value <0.05). Additionally, depression, irritability, apathy, and motor symptoms had SSA with the year of HD diagnosis. Conclusions Neuropsychiatric symptoms are prevalent in individuals with HD. The high incidence of suicidal behavior in this cohort is noteworthy. Depression, apathy, irritability, and motor symptoms can manifest years before diagnosis, indicating a delay in treatment, genetic counseling, and family support. Remarkably, individuals with a higher RL seem more susceptible to violent behavior. To better establish these correlations, we need to expand our sample size of HD patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".