An update of palliative care in lung transplantation with a focus on symptoms, quality of life and functional outcomes
Bibliographic record
Abstract
PURPOSE OF REVIEW: Palliative care (PC) in lung transplantation is increasingly acknowledged for its important role in addressing symptoms, enhancing functionality, and facilitating advance care planning for patients, families, and caregivers. The present review provides an update in PC management in lung transplantation. RECENT FINDINGS: Research confirms the effectiveness of PC for patients with advanced lung disease who are undergoing transplantation, showing improvements in symptoms and reduced healthcare utilization. Assessment tools and patient-reported outcome measures for PC are commonly used in lung transplant candidates, revealing discrepancies between symptom severity and objective measures such as exercise capacity. The use of opioids to manage dyspnea and cough in the pretransplant period is deemed safe and does not heighten risks posttransplantation. However, the integration of PC support in managing symptoms and chronic allograft dysfunction in the posttransplant period has not been as well described. SUMMARY: Palliative care support should be provided in the pretransplant and select peri-operative and posttransplant periods to help support patient quality of life, symptoms, communication and daily function.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".