Assessing the socio-economic burden of inherited and inflammatory neuromuscular diseases (BIND study): a study protocol
Bibliographic record
Abstract
INTRODUCTION: Neuromuscular diseases (NMDs) are rare multisystem, genetic or acquired disorders causing weakness and/or sensory loss. It is essential for governments, insurance providers, and broader society to have a better understanding of the burden of illness of NMDs. Our goal is to assess the social and economic burden of Canadians living with NMDs, encompassing schooling and education achievement, health-related quality-of-life, and labour force participation and productivity. METHODS AND ANALYSIS: We will conduct a national, cross-sectional survey of individuals living with a NMD and their caregivers who are members of Muscular Dystrophy Canada and/or are patients within our national network of neuromuscular clinics. Surveys can be completed online or via telephone. The specific sub-sections of the questionnaire will differ based on respondent's profile, whether they are 1) a minor living with a NMD, 2) an adult living with a NMD, 3) an adult who is a caregiver for someone living with a NMD, or 4) an adult who both lives with a NMD and is a caregiver for someone with a NMD. We will use descriptive statistics to describe distributions and ranges of the social and economic measures. Pearson correlations for continuous data and Spearman rho for rank data will be used to detect the strength of association of socio-demographic factors, disease characteristics, and social and economic impacts of NMDs. ETHICS AND DISSEMINATION: The study protocol has been approved by the Ottawa Health Science Network Research Ethics Board (Protocol ID # 20210601-01H). This study will provide the overall impact of NMD on costs and health-related quality of life, disseminated via a series of manuscripts which will include both between- and within-NMD/NMD subtype comparisons. The data obtained will guide governmental policy development and inform patient organisation programs to deliver more effective supports to individuals and families affected by NMDs.
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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 | 0.038 | 0.019 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.053 | 0.013 |
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".