Improvement in Health‐Related Quality of Life After Lung Transplantation
Bibliographic record
Abstract
BACKGROUND/OBJECTIVE: Traditional survival outcomes do not reflect the effects on the health-related quality of life (HRQL) of patients. HRQL following lung transplantation has not been studied systematically. The Health Utilities Index (HUI) is a family (HUI2 and HUI3) of measures of HRQL that has not been previously used to assess HRQL in lung transplantation. The objective of the present study was to assess the impact of lung transplantation on patient's HRQL using the HUI. METHODS: A total of 43 patients completed a battery of questionnaires before lung transplantation, and at three months and six months after lung transplantation. The 15-item questionnaire (HUI2 and HUI3) was used. Overall scores were based on a conventional scale (0.00 = dead, 1.00 = perfect health). Mental health was assessed by the Hospital Anxiety and Depression Scale. Adherence to medication and exercise were assessed by Morisky's and Godin's questionnaires, respectively. RESULTS: Sixty-five per cent of the patients were men, with a mean age of 53 years (range 18 to 67 years). The mean overall HUI3 score for the lung transplant candidates (0.57) was much lower than for the lung transplant recipients (0.82) at six months post-transplantation. This difference was clinically important and statistically significant (P<0.05 [paired t test, degrees of freedom (df) = 35]). Differences in mean Hospital Anxiety and Depression Scale scores after transplantation were statistically significant (P<0.05 [paired t test, df=35]). After six months, transplant recipients were more adherent to medication (P<0.05 [X2 test, df=1]). Recipients were able to increase the duration of exercise at all levels of intensity. CONCLUSION: Lung transplantation improved the patients' HRQL and adherence to medication. Anxiety levels persisted six months after transplantation but depression levels had decreased significantly.
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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 | 0.002 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".