Confluent fibrosis and fibroblast foci in fibrotic non‐specific interstitial pneumonia
Bibliographic record
Abstract
AIMS: The separation of fibrotic non-specific interstitial pneumonia (FNSIP) and usual interstitial pneumonia (UIP) is important for patient treatment and prognosis, but is sometimes a difficult diagnostic problem. Most authors believe that fibroblast foci are rare in NSIP, and that the finding of multiple fibroblast foci suggests a diagnosis of UIP. Similarly, architectural distortion is viewed as favouring a diagnosis of UIP. This study aims to assess these criteria for their diagnostic utility. METHODS AND RESULTS: We report eight patients with a high-resolution computed tomography diagnosis of FNSIP, and a picture of fibrotic NSIP on biopsy, but in whom, in all cases, fibrosis focally widened the walls to the point of confluence, producing architectural distortion in the form of variably sized, sometimes quite large, blocks of fibrosis, but not honeycombing. Fibroblast foci varied from four to nine per section, and point counting morphometry showed that the areas containing large blocks of confluent fibrosis were geographically strongly associated with fibroblast foci, whereas fibroblast foci were rare away from the confluent fibrosis. Follow-up imaging studies (mean interval 19.5 months; range 2-42 months) in six patients revealed stable or improved disease in four and worsening disease in two. No case had or developed radiological honeycombing, and there were no other imaging findings to suggest a diagnosis of UIP. CONCLUSIONS: Otherwise typical FNSIP cases can show architectural distortion caused by confluence or marked expansion of fibrotic alveolar walls. These areas tend to be associated with fibroblast foci. These findings do not imply a poor prognosis, and should not be confused with UIP.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".