Spectrum of chronic lung allograft dysfunction pathology in human lung transplantation
Bibliographic record
Abstract
BACKGROUND: Long-term survival after lung transplantation (LTx) remains limited by chronic lung allograft dysfunction (CLAD), which includes 2 main phenotypes: bronchiolitis obliterans syndrome (BOS) and restrictive allograft syndrome (RAS), with possible overlap. We aimed to detail and quantify pathological features of these CLAD sub-types. METHODS: Peripheral and central paraffin-embedded explanted lung samples were obtained from 20 consecutive patients undergoing a second LTx for CLAD, from 3 lobes. Thirteen lung samples, collected from non-transplant lobectomies or donor lungs, were used as controls. Blinded semi-quantitative grading was performed to assess airway fibrotic changes, parenchymal and pleural fibrosis, and epithelial and vascular abnormalities. RESULTS: CLAD lung samples had higher scores for all airway- and lung-related parameters compared to controls. There was a notable overlap in histologic scores between BOS and RAS, with a wide range of scores in both conditions. Parenchymal and vascular fibrosis scores were significantly higher in RAS compared to BOS (p = 0.003 for both). We observed a significant positive correlation between the degree of inflammation around each airway, the severity of epithelial changes, and airway fibrosis. Immunofluorescence staining demonstrated a trend toward a lower frequency of club cells in CLAD and a higher frequency of apoptotic club cells in BOS samples (p = 0.01). CONCLUSIONS: CLAD is a spectrum of airway, parenchymal, and pleural fibrosis, as well as epithelial, vascular, and inflammatory pathologic changes, where BOS and RAS overlap significantly. Our semi-quantitative grading score showed a generally high inter-reader reliability and may be useful for future CLAD histologic assessments.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".