Chronic Pulmonary Microaspiration
Bibliographic record
Abstract
PURPOSE: The aim of the study was to describe the high-resolution computed tomography (CT) manifestations of chronic pulmonary microaspiration, a condition characterized by recurrent subclinical aspiration of small droplets of gastric contents or foreign particles into the lungs. MATERIALS AND METHODS: We reviewed the CT findings in 13 consecutive patients with clinical (n=13) and histologic (n=1) diagnosis of chronic pulmonary microaspiration. Twelve patients presented with persistent cough, but none had a clinical history of acute aspiration. One patient was asymptomatic. All patients had volumetric CT of the chest reconstructed using thin sections (1 to 1.3 mm) at the time of diagnosis. The CT scans were interpreted by 3 chest radiologists who reached a final decision by consensus. RESULTS: All 13 patients had centrilobular nodules and ground-glass opacities that involved mainly the dependent lung regions in 11 patients and had a random distribution in 2. Other common findings included branching opacities (n=10), small foci of consolidation (n=7), septal lines (n=5), and bronchiectasis (n=7). The 13 patients had at least 1 risk factor for aspiration including gastroesophageal reflux (n=9), hiatus hernia (n=6), esophageal dysfunction (n=3), oropharyngeal dysphagia (n=1), esophageal carcinoma (n=1), and use of sedatives (n=2). CONCLUSIONS: The high-resolution CT manifestations of chronic pulmonary microaspiration consist mainly of centrilobular nodules and ground-glass opacities that tend to involve predominately the dependent regions. Branching opacities and small foci of consolidation are seen in the majority of cases.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".