Neurocognitive signs in prodromal Huntington disease.
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: PREDICT-HD is a large-scale international study of people with the Huntington disease (HD) CAG-repeat expansion who are not yet diagnosed with HD. The objective of this study was to determine the stage in the HD prodrome at which cognitive differences from CAG-normal controls can be reliably detected. METHOD: For each of 738 HD CAG-expanded participants, we computed estimated years to clinical diagnosis and probability of diagnosis in 5 years based on age and CAG-repeat expansion number (Langbehn, Brinkman, Falush, Paulsen, & Hayden, 2004). We then stratified the sample into groups: NEAR, estimated to be ≤9 years; MID, between 9 and 15 years; and FAR, ≥15 years. The control sample included 168 CAG-normal participants. Nineteen cognitive tasks were used to assess attention, working memory, psychomotor functions, episodic memory, language, recognition of facial emotion, sensory-perceptual functions, and executive functions. RESULTS: Compared with the controls, the NEAR group showed significantly poorer performance on nearly all of the cognitive tests and the MID group on about half of the cognitive tests (p = .05, Cohen's d NEAR as large as -1.17, MID as large as -0.61). One test even revealed significantly poorer performance in the FAR group (Cohen's d = -0.26). Individual tasks accounted for 0.2% to 9.7% of the variance in estimated proximity to diagnosis. Overall, the cognitive battery accounted for 34% of the variance; in comparison, the Unified Huntington's Disease Rating Scale motor score accounted for 11.7%. CONCLUSIONS: Neurocognitive tests are robust clinical indicators of the disease process prior to reaching criteria for motor diagnosis of HD.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it