Idiopathic pulmonary fibrosis: state of the art for 2023
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Idiopathic pulmonary fibrosis (IPF) is a progressive fibrotic lung disease characterised by worsening respiratory symptoms and physiological impairment. Increasing awareness of the clinical manifestations of IPF, more widespread use of computed tomography scans and other potential factors have contributed to a rising prevalence of IPF over the last two decades, especially among people over the age of 65 years. Significant advances in the understanding of the pathobiology of IPF have emerged, and multiple genetic and nongenetic contributors have been identified. The individual patient course and the rate of disease progression in IPF are often unpredictable and heterogeneous. The rate of lung function decline is further modified by treatment with antifibrotic therapies, which have been shown to slow down disease progression. The presence of comorbid conditions may increase symptom burden and impact survival. Clinical monitoring at regular intervals to assess for disease progression by worsening symptoms, physiological parameters and/or radiological features is essential to assess the natural disease course and to guide further management, including prompt detection of complications and comorbid conditions that warrant additional treatment considerations, and timely consideration of referral to palliative care and lung transplantation for the appropriate patient. More studies are needed to determine whether early detection of IPF might improve patient outcomes. The purpose of this concise clinical review is to provide an update on IPF diagnosis, epidemiology, natural history and treatment in the context of new knowledge and latest clinical practice guidelines.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 it