Churg-Strauss Syndrome
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to evaluate high-resolution CT findings in 7 patients with Churg-Strauss syndrome and to compare the CT with the histopathologic findings. MATERIALS AND METHODS: High-resolution CT scans of 7 asthmatic patients (4 women, 3 men, age range, 34-62 years, mean 49 years) with Churg-Strauss syndrome were reviewed by 2 observers. Histologic specimens of lung obtained at surgical (n = 3) or transbronchial (n = 3) biopsy or autopsy (n = 1) were reviewed by an expert lung pathologist. The diagnosis of Churg-Strauss was based on clinical, laboratory, and histologic findings. RESULTS: Parenchymal and airway abnormalities included ground-glass opacities (n = 5), areas of air-space consolidation (n = 4), centrilobular nodules (n = 5), nodules 1-3 cm in diameter (n = 3), interlobular septal thickening (n = 4), bronchial wall thickening (n = 4), and areas of atelectasis (n = 1). Surgical biopsy (n = 3) and autopsy (n = 1) specimens demonstrated airspace disease in 3 patients, interlobular septal thickening in 3 patients, and airway abnormalities in 2 patients. Histologically, the airspace disease included eosinophilic pneumonia (n = 2) and small foci of organizing pneumonia (n = 1). The septal thickening was due to edema combined with numerous (n = 2) or few (n = 1) eosinophils. The airway abnormalities (n = 2) included muscle hypertrophy and large airway wall necrosis (n = 1) and eosinophilic infiltration of the airway walls (n = 1). Transbronchial biopsy (n = 3) demonstrated increased eosinophils. CONCLUSION: The main high-resolution CT findings of Churg-Strauss syndrome consist of airspace consolidation or ground-glass opacities, septal lines, and bronchial wall thickening. These reflect the presence of eosinophilic infiltration of the airspaces, interstitium, and airways, and interstitial edema.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| 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".