The construct validity of the health utilities index mark 3 in assessing health status in lung transplantation
Bibliographic record
Abstract
PURPOSE: To assess the cross-sectional construct validity of the Health Utilities Index Mark 3 (HUI3) in lung transplantation. METHODS: Two hundred and thirteen patients (103 pre-transplant and 110 post-transplant) with mean age 53 years old (SD 13) were recruited during a randomized controlled clinical trial at the out-patient clinic in a tertiary institution. At baseline, patients self-completed measures that included the HUI3, EuroQol EQ-5D, Hospital Anxiety and Depression Scale (HADS) and socio-demographic questionnaire. Six-minute walk test scores and forced expiratory volume in 1 second data were collected from patient's medical records. A priori hypotheses were formulated by members of the transplant team about the expected degree of association between the measures. Correlation coefficients of < 0.1 were considered as negligible, 0.1 to < 0.3 as small, 0.3 to < 0.5 as medium, and ≥ 0.5 as large. RESULTS: Of the ninety predictions made, forty three were correct but in 31 the correlation was slightly lower than predicted and in 7 the correlations were much higher than predicted. In 48% of the cases, predicted and observed associations were in agreement. Predictions of associations were off by one category in 42% of the cases; in 10% of the cases the predictions were off by two categories. CONCLUSIONS: This is the first study providing evidence of cross-sectional construct validity of HUI3 in lung transplantation. Results indicate that the HUI3 was able to capture the burden of lung disease before transplantation and that post-transplant patients enjoyed higher health-related quality of life than pre-transplant patients.
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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 | 0.019 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".