Diffuse Lung Disease in Young Children
Bibliographic record
Abstract
RATIONALE: Considerable confusion exists regarding nomenclature, classification, and management of pediatric diffuse lung diseases due to the relative rarity and differences in the spectrum of disease between adults and young children. OBJECTIVES: A multidisciplinary working group was formed to: (1) apply consensus terminology and diagnostic criteria for disorders presenting with diffuse lung disease in infancy; and (2) describe the distribution of disease entities, clinical features, and outcome in young children who currently undergo lung biopsy in North America. METHODS: Eleven centers provided pathologic material, clinical data, and imaging from all children less than 2 years of age who underwent lung biopsy for diffuse lung disease from 1999 to 2004. MEASUREMENTS AND MAIN RESULTS: Multidisciplinary review categorized 88% of 187 cases. Disorders more prevalent in infancy, including primary developmental and lung growth abnormalities, neuroendocrine cell hyperplasia of infancy, and surfactant-dysfunction disorders, constituted the majority of cases (60%). Lung growth disorders were often unsuspected clinically and under-recognized histologically. Cases with known surfactant mutations had characteristic pathologic features. Age at biopsy and clinical presentation varied among categories. Pulmonary hypertension, presence of a primary developmental abnormality, or ABCA3 mutation was associated with high mortality, while no deaths occurred in cases of pulmonary interstitial glycogenosis, or neuroendocrine cell hyperplasia of infancy. CONCLUSIONS: This retrospective cohort study identifies a diverse spectrum of lung disorders, largely unique to young children. Application of a classification scheme grouped clinically distinct patients with variable age of biopsy and mortality. Standardized terminology and classification will enhance accurate description and diagnosis of these disorders.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".