A liminal stage after predictive testing for Huntington disease
Bibliographic record
Abstract
BACKGROUND: Following predictive testing for Huntington disease (HD), knowledge of one's carrier status may have consequences on disease onset. Our study aimed to address two questions. First, does knowledge of being a carrier of the pathological HD mutation trigger onset of the disease? Second, does this knowledge influence self-awareness and allow carriers to identify signs and symptoms of disease onset? METHODS: Between 2012 and 2015, 75 HD mutation carriers were examined using the Unified Huntington's Disease Rating Scale (UHDRS) motor score. Onset estimation made with the disease burden score was compared with UHDRS findings. We collected qualitative data with questionnaires and semistructured interviews. RESULTS: 38 women and 37 men, aged 43.7 years±10.5 (20-68), were interviewed after a mean delay between test and study interview of 10.5 years±4.7 (from 4 to 21 years). Estimation of age at onset was 4.5±8.5 years earlier than data-derived age at onset. Participants were categorised according to their motor score: scores <5 were premanifest (n=35), and scores >5 were manifest carriers (n=40). Self-observation was a major preoccupation for all, independent of their clinical status (82% vs 74%, p=0.57). Among manifest carriers, 56% thought they showed symptoms, but only 33% felt ill. Interestingly, this was also observed in those without motor signs (20% and 9%). Being a mutation carrier did not significantly facilitate recognition of motor signs. Interviews with premanifest carriers allowed the burden of self-observation to be illustrated despite lack of motor signs. CONCLUSIONS: Estimating age at onset based on disease burden score may not be accurate. The transition to disease was experienced as an ambiguous or liminal experience. The view of mutation carriers is not always concordant with medical onset estimation, highlighting the difficulties involved in the concept of onset and its use as an outcome in future disease-modifying trials.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".