What Happens to Frailty in the First Year After Lung Transplantation?
Bibliographic record
Abstract
BACKGROUND: Frailty is prevalent in lung transplant (LTx) candidates, but the impact and subsequent frailty trajectory is unclear. This study aimed to investigate frailty over the first year after LTx. METHOD: Post-LTx recipients completed a thrice weekly 12-week directly supervised exercise rehabilitation program. Edmonton Frail Scale (EFS) was used to assess frailty. Primary outcome was 6-Minute Walk Distance (6MWD) measured at pre-LTx, prerehabilitation, postrehabilitation, and 1 year post-LTx. RESULTS: 106 of 139 recruited participants underwent LTx: mean age 58 years, 48% male, 52% with chronic obstructive pulmonary disease. Mean (± SD) frailty scores pre-LTx and 1 year post-LTx were 5.54 ± 2.4 and 3.28 ±1.5. Mean 6MWD improved significantly for all: prerehabilitation 326 m (SD 116), versus postrehabilitation 523 m (SD 101) (p < 0.001) versus 1 year 512 m (SD 120) (p < 0.001). There were significant differences between an EFS > 7 (frail) and EFS ≤ 7 (not frail) for 6MWD, grip strength (GS), anxiety, and depression. Postrehabilitation, there were no significant differences in 6MWD, GS, anxiety, or depression while comparing EFS > 7 versus ≤ 7. At 1 year, there was a significant difference in depression but not 6MWD, GS, or anxiety between those EFS ≤ 7 and > 7 (p = 0.017). CONCLUSION: Participants in a structured post-LTx rehabilitation program improved in functional exercise capacity (6MWD), GS, depression, and anxiety. For frail participants exercise capacity, depression, anxiety, and GS were well managed in rehabilitation with no significant differences between those who were not frail. Pre-LTx frailty may be reversible post-LTx and should not be an absolute contraindication to LTx.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".