Idiopathic pulmonary fibrosis beyond the lung: understanding disease mechanisms to improve diagnosis and management
Bibliographic record
Abstract
Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive disorder with an estimated median survival time of 3-5 years after diagnosis. This condition occurs primarily in elderly subjects, and epidemiological studies suggest that the main risk factors, ageing and exposure to cigarette smoke, are associated with both pulmonary and extrapulmonary comorbidities (defined as the occurrence of two or more disorders in a single individual). Ageing and senescence, through interactions with environmental factors, may contribute to the pathogenesis of IPF by various mechanisms, causing lung epithelium damage and increasing the resistance of myofibroblasts to apoptosis, eventually resulting in extracellular matrix accumulation and pulmonary fibrosis. As a paradigm, syndromes featuring short telomeres represent archetypal premature ageing syndromes and are often associated with pulmonary fibrosis. The pathophysiological features induced by ageing and senescence in patients with IPF may translate to pulmonary and extrapulmonary features, including emphysema, pulmonary hypertension, lung cancer, coronary artery disease, gastro-oesophageal reflux, diabetes mellitus and many other chronic diseases, which may lead to substantial negative consequences in terms of various outcome parameters in IPF. Therefore, the careful diagnosis and treatment of comorbidities may represent an outstanding chance to improve quality of life and survival, and it is necessary to contemplate all possible management options for IPF, including early identification and treatment of comorbidities.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".