Systematic review of content and quality of idiopathic pulmonary fibrosis review articles
Bibliographic record
Abstract
Narrative reviews are frequently accessed; however, the content and quality of review articles on idiopathic pulmonary fibrosis (IPF) have not been assessed. A systematic review assessed content and quality of narrative review articles that addressed the diagnosis or management of IPF and were published from 2001 to 2015. Article recommendations were assessed relative to contemporary IPF guidelines. Quality was assessed using the DISCERN instrument. Articles were predominantly written by physicians and published in respiratory journals. Conflicts of interest and sources of funding were reported in 52% and 24% of reviews, respectively. European authors were more likely to recommend bronchoscopy (adjusted p=0.02) and were more likely to recommend pirfenidone or nintedanib prior to publication of definitive clinical trials (adjusted p=0.04). A total of 39% of management-focused articles suggested therapies that were never recommended in guidelines. Predictors of higher article quality were citation of the contemporary IPF guideline (p=0.01) and more recent publication (p=0.001). Quality of reviews increased over time; however, review articles frequently made discordant recommendations compared to IPF guidelines. These findings indicate the need for authors, peer reviewers, editors and readers to critically appraise the content and quality of narrative reviews on IPF, and the need for frequent guideline updates to reflect new evidence.
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 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 | 0.108 | 0.467 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.009 |
| Bibliometrics | 0.025 | 0.023 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".