337 Use of Endobronchial Valves for the Management of Bronchopleural Fistulas and Concomitant Empyema: Updated Insights to Clinical Outcomes, Efficacy, and Concerns
Bibliographic record
Abstract
Abstract Aim Bronchopleural fistulas (BPF), although rare, are fatal complications associated with a significant risk of mortality and morbidity. Endobronchial valves (EBVs) have emerged as a minimally invasive therapeutic option for BPFs, offering a means to seal air leaks and promote healing. Empyema, characterized by infected pleural fluid, has seen the use of EBVs to isolate infected areas and facilitate drainage. This narrative review aims to assess and synthesize the clinical outcomes, efficacy, and challenges of EBVs in managing BPFs and concomitant empyema, highlighting current evidence, pitfalls, and future directions. Method A narrative review was performed; PubMed, Ovid Medline, and Embase were systematically searched from inception till 2024 for peer-reviewed articles focusing on the use of EBVs for the management of BPFs and concomitant empyema. Relevant articles were screened, data extracted and summarized. Results EBVs have shown effectiveness in managing BPFs and persistent air leaks (PAL), with some studies reporting success rates exceeding 70%. Studies have reported immediate air leak cessation following EBV placement, particularly in critically ill, mechanically ventilated patients, with recovery times of 5 to 13 days. The most successful outcomes were seen in patients with fistulas ≤8mm. EBVs also proved useful in combination with minimally invasive surgical debridement for treating parapneumonic empyema with peripheral BPFs. Complications were minimal, including valve secretion adhesion and mild granulation tissue hyperplasia. Conclusions EBVs offer a promising treatment for BPFs and PALs, particularly in patients unfit for major thoracic surgery. Larger studies are needed to confirm the efficacy of EBVs in this population.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".