The Impact of Inadequate (“AX”) Transbronchial Biopsies on Post–lung Transplant CLAD or Death
Bibliographic record
Abstract
BACKGROUND: Procuring a good quality transbronchial-biopsy sample is essential for diagnosing acute cellular rejection after lung transplantation (LT). Insufficient transbronchial-biopsy samples are graded "AX." We hypothesized that AX samples may be associated with a higher risk for chronic lung allograft dysfunction (CLAD) or death/retransplant, through a potential anatomic or physiologic underlying pulmonary process or because of undiagnosed acute cellular rejection episodes. METHODS: We conducted a single-center, retrospective, cohort study drawn from all consecutive adult, first, bilateral LT between 1999 and 2015. We reviewed all biopsies obtained within the first year posttransplant and compared outcomes of patients with ≥1 AX to patients with no AX. Association of any AX or percent AX with time to CLAD or death/retransplant was assessed using Cox Proportional Hazards models. RESULTS: The cohort consisted of 809 patients with a median of 6 (interquartile range 5-6) biopsies and 16.7% (interquartile range 0-25) AX samples within the first year posttransplant. Four hundred thirty-nine (54.3%) subjects had ≥1 AX sample obtained within the time period. Median time to CLAD or death/retransplant, from 1 year posttransplant, was 761 (320, 1587) and 1200 (662, 2308) days, respectively. In the multivariable analysis, there was no difference in risk for CLAD (hazard ratio = 1.05, 95% confidence interval, 0.87-1.28, P = 0.60), or death/retransplant (hazard ratio = 1.14, 95% confidence interval, 0.92-1.42, P = 0.24) between patients with ≥1 AX biopsy versus none. Among subjects with ≥1 AX, having >50% AX biopsies was not associated with outcome. CONCLUSIONS: This is the first study to demonstrate that AX biopsies are not associated with an increased risk of CLAD or death/retransplant after LT and may not require to repeat the biopsy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".