Airway Oscillometry Detects Spirometric-Silent Episodes of Acute Cellular Rejection
Bibliographic record
Abstract
Abstract Rationale Acute cellular rejection (ACR) is common during the initial 3 months after lung transplant. Patients are monitored with spirometry and routine surveillance transbronchial biopsies. However, many centers monitor patients with spirometry only because of the risks and insensitivity of transbronchial biopsy for detecting ACR. Airway oscillometry is a lung function test that detects peripheral airway inhomogeneity with greater sensitivity than spirometry. Little is known about the role of oscillometry in patient monitoring after a transplant. Objectives To characterize oscillometry measurements in biopsy-proven clinically significant (grade ≥2 ACR) in the first 3 months after a transplant. Methods We enrolled 156 of the 209 double lung transplant recipients between December 2017 and March 2019. Weekly outpatient oscillometry and spirometry and surveillance biopsies at Weeks 6 and 12 were conducted at our center. Measurements and Main Results Of the 138 patients followed for 3 or more months, 15 patients had 16 episodes of grade 2 ACR (AR2) and 44 patients had 64 episodes of grade 0 ACR (AR0) rejection associated with stable and/or improving spirometry. In 15/16 episodes of AR2, spirometry was stable or improving in the weeks leading to transbronchial biopsy. However, oscillometry was markedly abnormal and significantly different from AR0 (P < 0.05), particularly in integrated area of reactance and the resistance between 5 and 19 Hz, the indices of peripheral airway obstruction. By 2 weeks after biopsy, after treatment for AR2, oscillometry in the AR2 group improved and was similar to the AR0 group. Conclusions Oscillometry identified physiological changes associated with AR2 that were not discernible by spirometry and is useful for graft monitoring after a lung transplant.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".