Medical Treatments for Idiopathic Pulmonary Fibrosis: a Protocol for a Systematic Review and Network Meta-analysis
Bibliographic record
Abstract
Abstract Background: Idiopathic pulmonary fibrosis (IPF) is a respiratory disorder of unknown etiology with a poor prognosis. There are novel therapies that have been studied in randomized controlled trials since the last network meta-analysis that may be of interest to academics and clinicians.Methods: We will perform a network meta-analysis on eligible randomized controlled trials of patients with IPF. We intend to search MEDLINE, EMBASE, Cochrane and clinicaltrials.org in order to complete a comprehensive search for adult IPF patients being treated with at least one of 21 of the selected medical therapies. A team will screen and extract eligible trials. We will perform Bayesian random-effects network meta-analysis. We will use GRADE and RoB 2.0 to assess the certainty and quality of the evidence. Discussion: There is a need for an updated meta-analysis on IPF medical therapies, including novel medical therapies. We intend on studying up to 21 medical therapies in the network meta-analysis to provide the most accurate and updated summary of the evidence for IPF treatments. Systematic review registrations: https://osf.io/afbhd/
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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 | 0.068 | 0.112 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.016 | 0.029 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.062 | 0.005 |
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".