Noninvasive Investigations for the Early Detection of Chronic Airways Dysfunction Following Lung Transplantation
Bibliographic record
Abstract
BACKGROUND: The diagnosis of chronic rejection after lung transplantation is limited by the lack of a reliable test to detect airways disease early. OBJECTIVES: To determine whether maximum midexpiratory flow (MMEF), or changes on high resolution computed tomography (HRCT) or ventilation/perfusion lung (V/Q) scans are sensitive and specific for early detection of bronchiolitis obliterans syndrome (BOS; forced expiratory volume in 1 s [FEV1] less than 80% post-transplant baseline) by evaluating long term survivors of lung transplantation at two sequential time points. METHODS: Twenty-two stable lung transplant recipients underwent spirometry, HRCT scanning and V/Q scanning 1.6 +/- 0.9 years and 3.1 +/- 1.1 years post-transplant (time points 1 and 2, respectively; mean +/- SD). RESULTS: Although HRCT was sensitive for the detection of BOS, it lacked specificity, and hence, there were no significant relationships between the presence of BOS and any of the HRCT parameters evaluated at time 1 or time 2. Of the V/Q parameters studied, the presence of heterogeneous perfusion (P=0.04, sensitivity 100%, specificity 33%) and segmental perfusion defects (P=0.04, sensitivity 60%, specificity 83%) were significantly related to BOS, but only at time 2. MMEF less than or equal to 75% post-transplant baseline was significantly related to the presence BOS at time 1 only (P=0.05, sensitivity 100%, specificity 47%). MMEF less than or equal to 75% post-transplant baseline at time 1 was sensitive for the development of BOS at time 2, but was limited by low specificity. CONCLUSIONS: In this group of lung transplant recipients, HRCT and V/Q scanning, as well as analysis of MMEF, did not add information that was clinically more useful than FEV1 for the early identification of chronic rejection.
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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 | 0.001 | 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 | 0.001 | 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".