Frailty Phenotypes, Disability, and Outcomes in Adult Candidates for Lung Transplantation
Bibliographic record
Abstract
RATIONALE: Frailty is associated with morbidity and mortality in abdominal organ transplantation but has not been examined in lung transplantation. OBJECTIVES: To examine the construct and predictive validity of frailty phenotypes in lung transplant candidates. METHODS: In a multicenter prospective cohort, we measured frailty with the Fried Frailty Phenotype (FFP) and Short Physical Performance Battery (SPPB). We evaluated construct validity through comparisons with conceptually related factors. In a nested case-control study of frail and nonfrail subjects, we measured serum IL-6, tumor necrosis factor receptor 1, insulin-like growth factor I, and leptin. We estimated the association between frailty and disability using the Lung Transplant Valued Life Activities disability scale. We estimated the association between frailty and risk of delisting or death before transplant using multivariate logistic and Cox models, respectively. MEASUREMENTS AND MAIN RESULTS: Of 395 subjects, 354 completed FFP assessments and 262 completed SPPB assessments; 28% were frail by FFP (95% confidence interval [CI], 24-33%) and 10% based on the SPPB (95% CI, 7-14%). By either measure, frailty correlated more strongly with exercise capacity and grip strength than with lung function. Frail subjects tended to have higher plasma IL-6 and tumor necrosis factor receptor 1 and lower insulin-like growth factor I and leptin. Frailty by either measure was associated with greater disability. After adjusting for age, sex, diagnosis, and transplant center, both FFP and SPPB were associated with increased risk of delisting or death before lung transplant. For every 1-point worsening in score, hazard ratios were 1.30 (95% CI, 1.01-1.67) for FFP and 1.53 (95% CI, 1.19-1.59) for SPPB. CONCLUSIONS: Frailty is prevalent among lung transplant candidates and is independently associated with greater disability and an increased risk of delisting or death.
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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 | 0.001 | 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 | 0.001 |
| 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".