Late Breaking Abstract - Assessing Chronic Lung Allograft Dysfunction (CLAD) Risk Using A Combined Physiology Score
Bibliographic record
Abstract
Introduction: Early predictors of CLAD, defined as a sustained >3 month FEV1 decline to ≤ 80% of the highest value post-lung transplant (LTx), have not been identified. Oscillometry, a novel pulmonary function test that is highly sensitive to lung mechanics, provides complementary information to spirometry. We previously developed a combined spirometry-oscillometry “SpirOsc” score, composed of %FEV1, FEV1/FVC, R5 (resistance at 5 Hz) z-score, R5-19 (difference from 5 to 19 Hz), and AX (area under reactance) at 3 months post-LTx, that is highly associated with CLAD. Aim: To evaluate the 3-month SpirOsc score for risk assessment of future CLAD. Methods: First-time double LTx recipients (2017-2021) with paired oscillometry spirometry at 3 months post-LTx (n=391). Patients were censored at time of CLAD onset or last spirometry before Feb 2025. Individual SpirOsc scores were calculated using pre-defined cutoff values for each parameter: 0 if below or 1 above the CLAD threshold. The relative contributions of spirometry and oscillometry were assessed by comparing: A) both normal, B) spirometry-only abnormal, C) oscillometry-only abnormal and D) both abnormal. A Cox hazards model assessed the hazard ratio (HR) for CLAD after adjusting for known factors. Results: Peri-operative demographics were similar between the 156 CLAD and 235 CLAD-free patients, except CLAD were younger. CLAD had lower %FVC and %FEV1. Higher SpirOsc scores were associated with greater CLAD risk (score 5 vs 0; adjusted HR 3.18 [1.16-6.26]). Both abnormal oscillometry-spirometry had greater risk (adjusted HR 2.54 [1.36-4.76]) than both normal. Conclusions: Higher SpirOsc scores provides early risk assessment of future 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".