Idiopathic Nonspecific Interstitial Pneumonia
Bibliographic record
Abstract
RATIONALE: The 2002 American Thoracic Society/European Respiratory Society classification of idiopathic interstitial pneumonias identified nonspecific interstitial pneumonia (NSIP) as a provisional diagnosis. Concern was expressed that NSIP was a "wastebasket" category, difficult to distinguish from other idiopathic interstitial pneumonias. OBJECTIVES: The following questions were addressed: (1) Is idiopathic NSIP a distinct entity? 2) If so, what are its clinical, radiologic and pathologic characteristics? (3) What is the role of radiology and pathology in establishing the diagnosis? (4) To make a diagnosis of idiopathic NSIP, what other disorders need to be excluded and how should this be done? METHODS: Investigators who had previously reported cases of idiopathic NSIP were invited to submit cases for review (n = 305). After initial review, cases with complete clinical, radiologic, and pathologic information (n = 193) were reviewed in a series of workshops. MEASUREMENTS AND MAIN RESULTS: Sixty-seven cases were identified as NSIP. Mean age was 52 years, 67% were women, 69% were never-smokers, and 46% were from Asian countries. The most common symptoms were dyspnea (96%) and cough (87%); 69% had restriction. By high-resolution computed tomography, the lower lung zones were predominantly involved in 92% of cases; 46% had a peripheral distribution; 47% were diffuse. Most showed a reticular pattern (87%) with traction bronchiectasis (82%) and volume loss (77%). Lung biopsies showed uniform thickening of alveolar walls with a spectrum of cellular to fibrosing patterns. Five-year survival was 82.3%. CONCLUSIONS: Idiopathic NSIP is a distinct clinical entity that occurs mostly in middle-aged women who are never-smokers. The prognosis of NSIP is very good.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".