Evidence of a disability paradox in patient‐reported outcomes in haemophilia
Bibliographic record
Abstract
INTRODUCTION: People with inherited and long-term conditions such as haemophilia have been shown to adapt to their levels of disability, often reporting better quality of life (QoL) than expected from the general population (the disability paradox). AIM: To investigate the disability paradox in people with haemophilia in the United States by examining preference differences in health state valuations versus the general population. METHODS: We conducted a discrete choice experiment including duration to capture valuations of health states based on patient-reported preferences. Participants indicated their preferences for hypothetical health states using the EQ-5D-5L, where each participant completed 15 of the 120 choice tasks. Response inconsistencies were evaluated with dominated and repeated scenarios. Conditional-logit regressions with random sampling of the general population responses were used to match the sample of patients with haemophilia. We compared model estimates and derived preferences associated with EQ-5D-5L health states. RESULTS: After removing respondents with response inconsistencies, 1327/2138 (62%) participants remained (177/283 haemophilia; 1150/1900 general population). Patients with haemophilia indicated higher preference value for 99% of EQ-5D-5L health states compared to the general population (when matched on age and gender). The mean health state valuation difference of 0.17 indicated a meaningful difference compared to a minimal clinically important difference threshold of 0.07. Results were consistent by haemophilia type and severity. CONCLUSION: Our findings indicated the presence of a disability paradox among patients with haemophilia, who reported higher health states than the general population, suggesting the impact of haemophilia may be underestimated if general population value sets are used.
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 | 0.040 | 0.113 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".