Change in Health‐Related Quality of Life in Youth with Chronic Hepatitis B Living in North America: A 5‐Year Cohort Study
Bibliographic record
Abstract
BACKGROUND: Greater hepatitis-related symptomology is associated with lower health-related quality-of-life (HRQoL) among untreated youth with chronic hepatitis B (CHB). How HRQoL changes over time in this population is unknown. METHODS: Children from 7 hepatology centers in North America positive for hepatitis B surface antigen, not taking anti-viral therapy, were enrolled in the Hepatitis B Research Network. A validated self-report HRQoL measure, the Child Health Questionnaire Child Report (CHQ-CF87), was completed annually by participants 10-17 years, with demographic variables, liver disease symptoms, and laboratory tests. Linear mixed-effects models were used to evaluate the 10 CHQ-CF87 subscale scores over 5 years among participants who completed the CHQ-CF87 at least twice. RESULTS: Participants (N = 174) completed the CHQ-CF87 a median of 4 times. Median age was 12 years (interquartile range: 10-14) at baseline; 60% were female, 79% Asian, and 47% adopted. The CHQ-CF87 subscale scores were high at baseline (median range: 75.4-100) and did not differ by time point, except for the Family Activities subscale (mean [95% CI]: 82.3 [79.8-84.8] at baseline; 90.8 [86.1-94.6] week 240). Most subscale scores lacked sufficient individual-level variability in change over time to evaluate predictors. Being White versus Asian predicted a more favorable change in Behavior (6.5 [95% CI: 2.0-11.0]). Older age predicted less favorable change in Mental Health (-0.8 [95% CI: -1.36 to -0.23] per year). Changes in liver enzymes and hepatitis B antigens, DNA, or symptom count were not related to changes in these subscale scores. CONCLUSION: HRQoL was generally good and consistent across 5 years in youth with CHB.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".