Characterization of Graft Injury by Respiratory Oscillometry following Lung Transplantation
Bibliographic record
Abstract
Long-term survival after lung transplantation is limited by the development of chronic lung allograft dysfunction (CLAD), with acute cellular rejection (ACR) being a significant contributing risk factor. Earlier identification and treatment of ACR are facilitated by routine monitoring with spirometry. Our previous results showed higher sensitivity of oscillometry in detecting graft injury associated with ACR compared to spirometry. As such, we hypothesized that oscillometry is a metric sensitive to ACR- and CLAD-associated injuries. We evaluated association between oscillometry, ongoing graft injury and risk of CLAD development in the post-lung transplant cohort. Our results revealed that the variance in oscillometry was significantly associated with a cumulative rejection index, A-score. The higher intra-subject variance in X5, AX and R5-19 was independently predictive of subsequent CLAD development. We concluded that oscillometry is a sensitive biomarker of ongoing graft injury following lung transplantation and may assist in identifying recipients at increased risk for CLAD.
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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 | 0.001 |
| 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 | 0.001 | 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".