Bronchiectasis: literature review for preparation of 2024 clinical guidelines
Bibliographic record
Abstract
Bronchiectasis, ICD-10 – J47, (BE) is a chronic respiratory disease characterized clinically by cough, sputum production and bronchial infection, and radiographically by abnormal and persistent dilation of the bronchi. Common causes include cystic fibrosis, primary ciliary dyskinesia, immune disorders, systemic inflammatory diseases and infections, and other factors. However, some cases are idiopathic, when the cause cannot be identified. In practice, patients with bronchiectasis are divided into two groups: associated and not associated with cystic fibrosis. The prevalence of the disease varies significantly worldwide; it is not reliably known in the Russian Federation. The aim of the review is to analyze the literature data on modern approaches to the diagnosis of BE and to familiarize readers with diagnostic methods and basic approaches to the treatment. Methods. Data from 77 articles and the expert opinion of specialists providing care to patients with BE were used. Results. The main causes, frequency of occurrence, clinical phenotypes and treatment approaches for BE are described. There are many clinical, laboratory, instrumental and radiological features that provide insight into the etiology of BE. The European consensus is that the goal of treating BE is to restore or maintain normal lung function. There are no randomized trials on the treatment of BE, so all treatment guidelines are based on very low-level evidence or extrapolated from cystic fibrosis guidelines. Recommendations for mucolytic, antibacterial and anti-inflammatory therapy for BE are described, taking into account international and national experience. Conclusion. The development of a new version of clinical guidelines with modern relevant information will improve the diagnosis and treatment of BE in the Russian Federation.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 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".