Describing the quality of life of boys with haemophilia in China: Results of a multicentre study using the <scp>CHO</scp>‐<scp>KLAT</scp>
Bibliographic record
Abstract
INTRODUCTION: The treatment of haemophilia varies across countries and across regions within some countries. Similar variation has been observed in health-related quality of life (HR-QoL). Relatively little is known about the HR-QoL of boys with haemophilia in China. AIM: The aim of this study was to describe the HR-QoL of boys with haemophilia in China using the Canadian Haemophilia Outcomes-Kids Life Assessment Tool (CHO-KLAT). METHODS: Boys (4-18 years of age) with haemophilia and their parents were enroled in a cross-sectional study. All parents/guardians of study subjects were requested to complete a CHO-KLAT questionnaire during a clinic visit, and report on several other clinical and socioeconomic factors in the past year. Boys who were > 7 years also completed the CHO-KLAT. RESULTS: A total of 269 parents of boys with haemophilia, from 13 hospitals in 12 provinces, were enroled during 2014. The boys ranged from 4.0 to 17.9 years of age; 91% had haemophilia A, most had moderate (52%) or severe (36%) disease, and most were receiving sub-optimal on-demand therapy or low-dose prophylactic therapy. Child self-report CHO-KLAT scores were available for 171 boys ≥7 years of age and ranged from 24.2 to 85.3 with a mean of 57.6 (n = 171). Parent proxy-reported CHO-KLAT scores ranged from 25.0 to 88.7 with a mean of 55.1 (n = 269). CONCLUSION: HR-QoL scores in boys with haemophilia in China were substantially lower than reported from Canadian and European boys with haemophilia. Longer term prospective studies are required to examine the factors impacting the HR-QoL for boys with haemophilia in China.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".