Radiographic Progression and Survival of the Different HRCT Patterns of Idiopathic Pulmonary Fibrosis.
Bibliographic record
Abstract
Introduction: Idiopathic pulmonary fibrosis (IPF) is a chronic disease with a peculiar (typical) HRCT pattern, but biopsy can demonstrate usual interstitial pneumonia in patients with atypical patterns. It is unknown how progression pattern varies among different radiographic presentations of IPF. We sought to investigate the longitudinal radiographic evolution and survival of typical and non-typical patterns. Materials and Methods: One-hundred-twenty-three patients diagnosed with IPF in 2 tertiary referral hospitals were included in the study. Longitudinal evolution of non-typical patterns was considered. The HRCT visual fibrosis score was used as a reliable evaluation tool of disease progression. HRCTs were scored by 2 senior chest radiologists with ILD expertise. The primary endpoint was the evolution of the presentation pattern to probable or typical. The secondary endpoint was lung transplant (LTx)-free survival from the time of diagnosis. Results: HRCT was 17±11 months. Four out of 45 (8.9%) patients with probable pattern "evolved" to a typical pattern of IPF, while 5 out of 31 (16.1%) with indeterminate/alternative pattern "evolved" to probable pattern. An average HRCT fibrosis score increase of 9±11% was observed with typical (n=49), 6±5% with probable (n=43) and 7±8% (n=31) with indeterminate/alternative presentation pattern. LTx-free survival and lung function declines did not show any difference related to presentation HRCT patterns. Conclusions: The evolution of a non-typical UIP pattern to a typical one is infrequent. All presentation HRCT patterns of IPF evolve in similar way and are associated with comparable survival time.[/sc].
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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 | 0.000 | 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) | 0.002 | 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".