Health‐Related Quality of Life in Egyptian Children With Haemophilia A and Chronic Arthropathy With the Era of Emicizumab Therapy: A Single‐Centre Cohort Study
Bibliographic record
Abstract
AIM: To assess the health-related quality of life (HRQOL) in children with haemophilia A and arthropathy before and after emicizumab prophylaxis using the Canadian Haemophilia Outcomes-Kids' Life Assessment Tool questionnaire Canadian Hemophilia Outcomes-Kids Life Assessment Tool (CHO-KLAT) v3.0 and haemophilia family impact tools (H-FIT). METHODS: Eighty-four children with haemophilia A and chronic arthropathy, recruited at Minia University HTC, and their parents/caregivers completed CHO-KLAT and H-FIT questionnaires before and after starting emicizumab. All patients underwent clinical and radiological joint assessments (HJHS, HEAD-US, CHAQ). Only 44 of them were confirmed to have chronic haemophilic arthropathy. RESULTS: After emicizumab prophylaxis, pain scores decreased significantly (p = 0.0001), while H-FIT scores and CHO-KLAT domain scores (physical activities, bleeding, knowledge, social functioning, treatment, autonomy, environment) increased significantly (p ≤ 0.002 for autonomy/environment; p = 0.0001 for others and total CHO-KLAT). Comparing arthropathic (n = 44) and non-arthropathic (n = 40) patients after initiation of emicizumab, the arthropathic group had significantly higher pain scores and lower H-FIT scores (p = 0.001) but similar total CHO-KLAT scores (p = 0.63). Following emicizumab initiation and implementation of a planned physiotherapy program in the arthropathic group, significant reductions occurred in pain scores, HJHS, HEAD-US, and CHAQ scores (p = 0.0001 for all). No significant correlation existed between the total CHO-KLAT score and HJHS or HEAD-US scores before or after emicizumab administration. CONCLUSION: Emicizumab prophylaxis significantly improved HRQoL and reduced joint pain in children with haemophilia A and chronic arthropathy. When combined with a planned physiotherapy program, it further leads to significant improvements in objective joint health outcomes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".