Clinical markers of early disease in persons near onset of Huntington’s disease
Bibliographic record
Abstract
OBJECTIVE: There is increasing evidence that neuron loss precedes the phenotypic expression of Huntington's disease (HD). As genes for late-onset neurodegenerative diseases are identified, the need for accurate assessment of phenoconversion (i.e., the transition from health to the disease phenotype) will be important. METHODS: Prospective longitudinal evaluation using the Unified Huntington's Disease Rating Scale (UHDRS) was conducted by Huntington Study Group members from 36 sites. There were 260 persons considered "at risk" for HD who initially did not have manifest disease and had at least one subsequent evaluation. Repeat UHDRS data, obtained an average of 2 years later, showed that 70 persons were given a diagnosis of definite HD based on the quantified neurologic examination. RESULTS: Baseline cognitive performances were consistently worse for the at-risk group who demonstrated conversion to a definitive diagnosis compared with those who did not. Longitudinal change scores showed that the at-risk group who did not demonstrate manifest disease during the follow-up study period demonstrated improvements in all cognitive tests, whereas performances in the at-risk group demonstrating conversion to disease during the study declined across cognitive domains. CONCLUSIONS: Neuropsychological measures show impairment 2 years before the development of more manifest motor disease. Findings suggest that these brief cognitive measures administered over time may capture early striatal neural loss in HD.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".