Humanistic burden of problem joints for children and adults with haemophilia
Bibliographic record
Abstract
INTRODUCTION: The "problem joint" (PJ) concept was developed to address patient-centric needs for a more holistic assessment of joint morbidity for people with haemophilia (PwH). AIM: To quantify the humanistic burden of PJs in PwH to further support validation of the PJ outcome measure. METHODS: Multivariable regression models evaluated the relationship between PJs and health-related quality of life (HRQoL, EQ-5D-5L) and overall work productivity loss (WPL) using data from the 'Cost of HaEmophilia: a Socioeconomic Survey' population studies (adults: CHESS II, CHESS US+; children/adolescents: CHESS-Paeds). Covariates included were haemophilia severity, age, comorbidities and education. RESULTS: The CHESS II sample included 292 and 134 PwH for HRQoL and WPL analyses, mean age 38.6 years (39% ≥1 PJ, 61% none). CHESS US+ included 345 and 239 PwH for HRQoL and WPL, mean age 35 years (43% ≥1 PJ, 57% none). CHESS-Paeds included 198 PwH aged 4-17 (HRQoL only), mean age 11.5 years (19% ≥1 PJ, 81% none). In CHESS II and CHESS US+, presence of PJs was associated with worse HRQoL (Both p < .001). Few CHESS-Paeds participants had PJs, with no significant correlation with HRQoL. In CHESS II, upper body PJs were significantly correlated to WPL (p < .05). In CHESS US+, having ≥1 PJ or upper and lower body PJs were significantly correlated to WPL (vs. none; both p < .05). CONCLUSION: This study has shown a meaningful burden of PJs on PwH, which should be considered in clinical and health policy assessments of joint health.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".