Whole lung lavage therapy (WLL) of pulmonary alveolar proteinosis (PAP): A global survey of current practices and procedures
Bibliographic record
Abstract
Background: WLL, the current standard treatment for patients affected by PAP, is not a standardized procedure. Aim: To describe WLL as currently practiced with respect to the procedure, indications for its use, evaluation of therapeutic benefit, and complication rate. Methods: We developed a questionnaire on several aspects of WLL and performed a global survey among centers performing WLL in either pediatric and/or adulthood setting. Results: We have collected expert opinions from 20 centers in 14 countries performing WLL in adults and 10 centers in 6 countries performing WLL in pediatric patients.In about half of centres, WLL is performed under general anesthesia with a double-lumen endobronchial tube in two consecutive sessions (one lung per session), with an interval of 1-2 weeks between procedures. Other common aspects are indications in PAP, use of saline warmed to 37oC and drainage of Instilled fluid by gravity. Differences consisted of contraindications, methods and timing of follow up evaluation, choice of first lung to be lavaged, patient position, total volume of lavage per lung, use of chest percussion, timing of extubation following WLL, and lung isolation and lavage methods for small children. Conclusions: This international survey found that WLL is safe and effective as therapy of PAP. Results also indicate that standardization of the procedure is required.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".