Long‐term joint outcomes of regular low‐dose prophylaxis in Chinese children with severe haemophilia A
Bibliographic record
Abstract
OBJECTIVES: To explore the long-term joint outcomes of low-dose prophylaxis in Chinese children with severe haemophilia A and to analyse their related factors. METHODS: We retrospectively analysed follow-up data from 21 severe haemophilia A children on regular low-dose prophylaxis for 6-10 years. We used International Prophylaxis Study Group magnetic resonance imaging score (IPSG MRI score), Hemophilia Joint Health Score (HJHS), number of target joints, and Hemophilia-Specific Quality of Life Index (Haemo-QoL) to evaluate joint outcomes. Factors associated with these outcomes were evaluated by statistical analysis. RESULTS: (1) The children were 1.75 to 17 years age at prophylaxis initiation. Median prophylactic factor VIII dose was 22.9 IU/kg per week. (2) At the end of follow-up: (a) The total IPSG MRI scores were 2-24 with 90.5% children exhibiting moderate to severe joint involvement (score 7-24); (b) The HJHS ranged 2-27, with 0-10 for 46.7% children and >10 for 53.3% children. There was a positive correlation between the MRI score and HJHS (p < .05); (c) Compared to their on-demand treatment period before prophylaxis, target joints numbers decreased, and no child needed auxiliary devices to walk; (d) Joint outcomes were positively correlated with the age at initiation of low-dose prophylaxis (p < .05) and negatively correlated with the treatment dose. CONCLUSION: Long-term low-dose prophylaxis had positive effect on joint outcomes compared with on-demand treatment. However, a certain degree of joint damage remained in all children indicating the need for improving the current strategy of low-dose prophylaxis.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".