Health utilities in adults with hemophilia A: A retrospective cohort study
Bibliographic record
Abstract
INTRODUCTION: Haemophilia A negatively affects a patient's quality of life. There is a limited amount of health utility data (a measure of health-related quality of life) available for patients with haemophilia A. This information is crucial for cost-effectiveness analysis for haemophilia A treatment. OBJECTIVES: The goal of this project is to elicit the health utilities and factors impacting utility values for haemophilia A patients in Canada. METHODS: This is a population-based, cross-sectional, retrospective study of health utilities in patients with haemophilia A using Patient Report Outcomes Burdens and Experiences (PROBE) components from the Canadian Bleeding Disorders Registry (CBDR). A review of the mean utilities for three severity states, defined by clotting factor VIII level, was completed. A multiple linear regression analysis was completed to examine the determinants of health utilities including age, treatment type, chronic pain status, number of limited joints, and bleed rate. RESULTS: The average utility values (and standard deviations) for patients with haemophilia A in Canada are .79(.17), .76(.20), and .77(.19) for patients with severe, moderate, and mild haemophilia. The regression showed chronic pain status and the number of additional comorbidities as major significant factors (p-value < .001) in haemophilia A utility. Haemophilia severity was shown to be a major factor with smaller p-value (p-value < .05). CONCLUSIONS: Haemophilia A patients have lower utility than the general population. Chronic pain was shown to be a significant, major factor in health-related quality of life. Our study is essential for valuing health outcomes in haemophilia A-related cost-effectiveness analysis.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".