Burden of Friedreich’s Ataxia to the Patients and Healthcare Systems in the United States and Canada
Bibliographic record
Abstract
OBJECTIVE: The study intended to substantiate healthcare resource utilization, costs, and funding patterns of US and Canadian Friedreich's Ataxia (FRDA) populations, to assess compliance with treatment guidance and to identify areas where novel healthcare measures or improved access to existing care may improve patients' functional and social capabilities and reduce the financial impact on the healthcare systems. METHODS: Healthcare resource utilization and costs were collected in a cross-sectional study in the US (N = 197) and Canada (N = 43) and analyzed across severity of disease categories. Descriptive statistics, correlation analysis, and hypothesis testing were applied. RESULTS: In the US, healthcare costs of FRDA patients were higher than those of "adults with two and more chronic conditions." Significantly higher costs were incurred in advanced stages of the disease, with paid homecare being the main driver. This pattern was also observed in Canada. Compliance with the recommended annual neurological and cardiological follow-up was high, but was low for the recommended regular speech therapy. In the US public and private funding ratios were similar for the FRDA and the general populations. In Canada the private funding ratio for FRDA was higher than average. CONCLUSION: The variety of healthcare measures addressing the broad range of symptoms of FRDA, and the increasing use of paid home care as disease progresses made total US healthcare costs of FRDA exceed the costs of US adults with two and more chronic conditions. Therefore, measures delaying disease progression will allow patients to maintain their independence longer and may reduce costs to the healthcare system. Novel measures to address dysarthria and to ensure access to them should be further investigated. The higher than average private funding ratio in Canada was due to the relatively high cost of the pharmacological treatment of FRDA.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".