Determinants of Health Utility in Lung and Heart-Lung Transplant Recipients
Bibliographic record
Abstract
Bronchiolitis obliterans syndrome (BOS) is associated with poor health-related quality of life (HRQL) following lung and heart-lung transplantation, but few other determinants of HRQL have been described. We performed a cross-sectional study of standard gamble utility, a preference-based measure of HRQL, in 90 stable lung and heart-lung transplant recipients. We used bivariate analyses and multiple linear regression to evaluate associations between utility scores and candidate predictor variables including age, sex, indication for transplant (obstructive, interstitial, suppurative and pulmonary vascular diseases), transplant type (bilateral, single and heart-lung),time since transplant, body mass index, arterial PO2,creatinine clearance, number of medications, presence of BOS and risk-attitude score. The median utility was 0.88 (inter-quartile range: 0.50–0.99).Multivariable analysis showed that female sex, absence of BOS, better renal function and longer time since transplantation were associated with higher utility scores, and that there were utility differences across diagnostic groups. Although BOS is a major determinant of utility following lung and heart-lung transplantation, other demographic and clinical factors are also associated with significant differences in this measure of HRQL. Bronchiolitis obliterans syndrome (BOS) is associated with poor health-related quality of life (HRQL) following lung and heart-lung transplantation, but few other determinants of HRQL have been described. We performed a cross-sectional study of standard gamble utility, a preference-based measure of HRQL, in 90 stable lung and heart-lung transplant recipients. We used bivariate analyses and multiple linear regression to evaluate associations between utility scores and candidate predictor variables including age, sex, indication for transplant (obstructive, interstitial, suppurative and pulmonary vascular diseases), transplant type (bilateral, single and heart-lung),time since transplant, body mass index, arterial PO2,creatinine clearance, number of medications, presence of BOS and risk-attitude score. The median utility was 0.88 (inter-quartile range: 0.50–0.99).Multivariable analysis showed that female sex, absence of BOS, better renal function and longer time since transplantation were associated with higher utility scores, and that there were utility differences across diagnostic groups. Although BOS is a major determinant of utility following lung and heart-lung transplantation, other demographic and clinical factors are also associated with significant differences in this measure of HRQL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".