Impact of liver transplantation on health-related quality of life
Bibliographic record
Abstract
This study is designed to measure the impact of orthotopic liver transplantation (OLT) on patients' health-related quality of life. Two types of health-related quality-of-life questionnaires were administered at baseline and after OLT: generic (Medical Outcomes Study Short Form 36) and liver specific (Chronic Liver Disease Questionnaire). We also recorded clinical, demographic, and laboratory data. Pre-OLT scores of liver transplant candidates were compared with those of the general population and patients with congestive heart failure (CHF) and chronic obstructive pulmonary disease (COPD). Thirty-seven liver transplant candidates were evaluated: 25 men and 12 women; age, 50.2 +/- 12 years; Child's class A, 3 patients; class B, 30 patients; class C, 4 patients; and galactose elimination capacity, 277 +/- 81. Health-related quality-of-life scores for patients awaiting liver transplants were significantly lower than those for patients with COPD and CHF and those in the general population. Sex and cause of liver disease did not affect the scores. There was a weak but significant inverse correlation between some aspects of health-related quality of life and both age (r = -0.31 to -0.34) and worsening of the Child-Pugh score (r = -0.32 to -0.43). All measured aspects of health-related quality of life significantly improved after OLT, and mental health scores were indistinguishable from the population norms. Similar improvements were evident in physical and disease-specific aspects of health-related quality of life, but some residual dysfunction persisted.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".