Correlation Between PFT and Oscillometry in Fibrotic Hypersensitivity Pneumonitis
Bibliographic record
Abstract
Abstract Rationale: Respiratory oscillometry, a pulmonary function tests (PFT) modality performed during tidal breathing, has not been well studied in patients with hypersensitivity pneumonitis (HP). Oscillometry measures respiratory impedance, a complex sum of resistance and reactance, and is sensitive to detecting changes in the lung parenchyma and small airways. Resistance measures the pressure generated to drive airflow while reactance reflects on the elastance of the lungs and chest wall. Previous studies showed that oscillometry is strongly correlated with idiopathic pulmonary fibrosis disease severity. Objective: To correlate conventional PFTs and respiratory oscillometry in HP. Methods: HP patients from the Toronto General Hospital ILD clinic, identified according to established guidelines, were assessed with oscillometry before clinically-indicated routine PFTs and six-minute walk test (6MWT). Polynomial regression modeling was used to evaluate the relationship between conventional PFTs and oscillometry. Results: 39 HP (18M/21F; mean±SD age=69±9 years) were enrolled from Oct 2022-Dec 2023. AX (area of reactance) demonstrated strongest correlation with RV (residual volume)/TLC (total lung capacity) ratio (Table1). FVC (forced vital capacity) was mostly strongly correlated with Xe I (reactance at end inspiratory) followed by X5in. (X5 during inspiration) and X5 (reactance at 5 Hz). Conclusion: AX correlated strongly with the RV/TLC, suggesting its usefulness in detecting peripheral ventilatory inhomogeneity in HP. FVC, the primary metric of disease progression was highly correlated with XeI and X5in. Thus, oscillometry can be used as an adjunct to PFTs in HP.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".