Antifibrotics in Non-Idiopathic Pulmonary Fibrosis Interstitial Lung Diseases
Bibliographic record
Abstract
Case 1 A 73-year-old male with a history of seronegative rheumatoid arthritis associated interstitial lung disease (RA-ILD), showing a probable usual interstitial pneumonia pattern of fibrosis, was seen for follow up. He had initially been started on mycophenolate for treatment of his ILD and remained stable on this treatment for a period; however, he later experienced slowly worsening dyspnea and cough over time. His pulmonary function tests (PFTs) demonstrated a 9.5% relative and 6% absolute decline in forced vital capacity (FVC) and a 12% relative and 10% absolute decline in diffusion capacity for carbon monoxide (DLCO) over the past 20 months. A computed tomography (CT) scan of the thorax showed some new changes of mild honeycombing in the right lower lobe (Figure 1). Case 2 A 50-year-old male developed dyspnea and cough after a COVID-19 infection. During the COVID-19 infection, his symptoms were mild and did not require treatment or hospitalization. A CT scan of the thorax demonstrated evidence of a fibrotic non-specific interstitial pneumonia pattern. Subsequent evaluation for new-onset ILD, included a surgical lung biopsy, which demonstrated organizing pneumonia with cicatricial changes. The patient received a course of prednisone, which led to a significant improvement in his symptoms but no improvement in imaging or PFTs. After tapering off prednisone, he required another course due to re-emergence of symptoms. However, retreatment yielded no improvement in his symptoms, imaging, or PFTs. The patient’s case, imaging, and pathology were reviewed in a multidisciplinary discussion, resulting in a diagnosis of organizing pneumonia evolving toward a more fibrotic phenotype. In addition to his worsening symptoms, imaging revealed increased reticulation, and assessments showed a significant decline in his FVC and DLCO over time.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".