Center variability in the prognostic value of a cumulative acute cellular rejection “A-score” for long-term lung transplant outcomes
Bibliographic record
Abstract
The acute rejection score (A-score) in lung transplant recipients, calculated as the average of acute cellular rejection A-grades across transbronchial biopsies, summarizes the cumulative burden of rejection over time. We assessed the association between A-score and transplant outcomes in 2 geographically distinct cohorts. The primary cohort included 772 double lung transplant recipients. The analysis was repeated in 300 patients from an independent comparison cohort. Time-dependent multivariable Cox models were constructed to evaluate the association between A-score and chronic lung allograft dysfunction or graft failure. Landmark analyses were performed with A-score calculated at 6 and 12 months posttransplant. In the primary cohort, no association was found between A-score and graft outcome. However, in the comparison cohort, time-dependent A-score was associated with chronic lung allograft dysfunction both as a time-dependent variable (hazard ratio, 1.51; P < .01) and when calculated at 6 months posttransplant (hazard ratio, 1.355; P = .031). The A-score can be a useful predictor of lung transplant outcomes in some settings but is not generalizable across all centers; its utility as a prognostication tool is therefore limited.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".