Pathologic Interpretation of Transbronchial Biopsy for Acute Rejection of Lung Allograft Is Highly Variable
Bibliographic record
Abstract
Despite the standardization of pathologic grading of acute rejection in transbronchial lung biopsies following lung transplantation, the reproducibility of pathologic diagnosis has not been adequately evaluated. To determine the interobserver variability for pathologic grading of acute rejection, 1566 biopsies from 845 subjects in the Lung Allograft Rejection Gene Expression Observational study were regraded by a pathology panel blinded to the original diagnosis and compared to the grade of acute rejection assigned by individual center pathologists. The study panel confirmed 49.1% of center pathologists' A0 grades, but upgraded 5.7% to A1 and 2.7% to grade ≥ A2 rejection; 42.5% were regraded as AX. Of 268 grade A1 samples, 21.2% were confirmed by the pathology panel; 18.7% were upgraded to ≥ A2 and 35.8% were downgraded to A0 with 24.3% being regraded as AX. Lastly, 53.5% of ≥ A2 cases were confirmed, but 15.7% were downgraded to grade A0 and 18.4% cases to A1, while 12.4% were regraded as AX. The kappa value for interobserver agreement was 0.183 (95%CI 0.147-0.220, p < 0.001). The results for B grade interpretation were similar. Suboptimal sampling is common and a high degree of variability exists in the pathologic interpretation of acute rejection in transbronchial biopsies.
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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 | 0.019 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".