Standard pulmonary function tests and respiratory oscillometry patterns in hypersensitivity pneumonitis and idiopathic pulmonary fibrosis
Bibliographic record
Abstract
BACKGROUND: Hypersensitivity pneumonitis (HP) is an interstitial lung disease (ILD) caused by repeated exposure to inhaled antigens, leading to small airway and parenchymal inflammation. Diagnosis is based on a detailed clinical history, chest imaging and invasive tests such as bronchoalveolar lavage. Distinguishing HP from other ILDs is challenging. Respiratory oscillometry, a novel pulmonary function test (PFT), is highly sensitive to small airway abnormalities. Oscillometry measurement of reactance is strongly correlated with gender-age-physiology score, a prognostic tool used to predict mortality and disease severity in idiopathic pulmonary fibrosis (IPF). OBJECTIVE: To determine if oscillometry and standard PFT patterns are different in HP and IPF. METHODS: 39 HP (79.5% with fibrotic HP) were enrolled from October 2022 to December 2023 for oscillometry before clinically-indicated standard PFTs and compared with 39 age-matched and sex-matched patients with IPF who also had same day oscillometry and standard PFTs. The main oscillometry metrics of interest were R5-19 (the difference in resistance from 5 to 19 Hz, a metric of small airway function and ventilatory inhomogeneity that increases with worsening respiratory mechanics), X5 (reactance at 5 Hz) which primarily reflects respiratory elastance and AX (area of reactance), a summative measure of the respiratory system stiffness across a range of frequencies, that behaves similarly but in opposite direction to X5. RESULTS: =0.64). CONCLUSION: Gas trapping (RV/TLC>0.40) is a feature of HP not observed in IPF. The strong correlations of RV/TLC with AX, X5 and R5-19 suggest that oscillometry can provide non-invasive markers of small airway obstruction in HP that can differentiate it from IPF.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".