Disease Burden of Huntington’s Disease (HD) on People Living with HD and Care Partners in Canada
Bibliographic record
Abstract
BACKGROUND: Huntington's disease (HD) has been shown to reduce health-related quality of life (HRQoL) and affect healthcare resource utilization (HRU) among patients and care partners internationally but has not been studied specifically in the Canadian context. OBJECTIVE: To characterize the burden of HD on individuals with HD and care partners of individuals with HD in Canada. METHODS: An online survey was distributed (September 14-November 23, 2020) through patient organizations to collect data on demographic and clinical characteristics, as well as: HRQoL, measured using the 36-Item Short-Form Health Survey (SF-36v1); HRU, measured using the Client Service Receipt Inventory (CSRI); and care partner burden, measured using the Caregiver Strain Index (CSI) and Huntington's Disease Quality of Life Battery for Carers (HDQoL-C). Descriptive statistics were used to report data and compare subgroups. RESULTS: A total of 62 adult individuals with HD (or their proxies) and 48 care partners met defined eligibility criteria. The mean [standard deviation] age was 51.2 [13.8] and 58.1 [13.9] years for individuals with HD and care partner respondents, respectively. For individuals with HD, the greatest HRQoL burden (i.e., lowest score) was for the SF-36v1 Role -Physical scale (46.8 [42.9]). HRU was higher for some services (e.g., general practitioner visits) for respondents who had experienced motor onset transition. Among care partners, 55.3% experienced high strain, as indicated by the CSI. The HDQoL-C showed the greatest HRQoL burden in feelings about life (45.1 [17.9]). CONCLUSION: This study quantified the substantial burden on individuals with HD and care partners in Canada, addressing a critical knowledge gap that can affect the availability of and access to healthcare services.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".