Bibliographic record
Abstract
Major risk factors for idiopathic pulmonary fibrosis (IPF) include older age and a history of smoking, which predispose to several pulmonary and extra-pulmonary diseases. IPF can be associated with additional comorbidities through other mechanisms as either a cause or a consequence of these diseases. We review the literature regarding the management of common pulmonary and extra-pulmonary comorbidities, including chronic obstructive pulmonary disease, lung cancer, pulmonary hypertension, venous thromboembolism, sleep-disordered breathing, gastroesophageal reflux disease, coronary artery disease, depression and anxiety, and deconditioning. Recent studies have provided some guidance on the management of these diseases in IPF; however, most treatment recommendations are extrapolated from studies of non-IPF patients. Additional studies are required to more accurately determine the clinical features of these comorbidities in patients with IPF and to evaluate conventional treatments and management strategies that are beneficial in non-IPF populations.
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 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) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".