Preoperative expectations for health‐related quality of life after lung transplant
Bibliographic record
Abstract
How patients' health-related quality of life (HRQL) after lung transplant compares to their preoperative expectations is unclear. As part of a previously published prospective cohort study, we compared 328 subjects' expectations for their post-transplant HQRL with and without chronic lung allograft dysfunction (CLAD) to their actual HRQL scores after transplant, using the visual analog scale (VAS) and standard gamble (SG). Subjects' expectations were considered met when the absolute difference between the expected and actual scores (the "expectation error") was <0.1 units, based on the minimally important difference for VAS and SG. On average, subjects' post-transplant HRQL without CLAD met their expectations (mean expectation error: -0.09 units [VAS] and +0.02 units [SG]) and subjects' post-transplant HRQL with CLAD met or exceeded their expectations (mean expectation error: +0.08 units [VAS] and +0.19 units [SG]). When subjects developed CLAD stages 1 and 2, their HRQL was better than they expected (mean expectation error of each disease group: >+0.1 units). When subjects developed CLAD stage 3, their HRQL was as they expected (mean expectation error of each disease group except COPD and CF: within ± 0.1 units). Patients' expectations for their HRQL after transplant are at least met and may be exceeded.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".