Outpatient selected lobar lavage: A novel approach to managing pulmonary alveolar proteinosis
Bibliographic record
Abstract
BACKGROUND Pulmonary alveolar proteinosis (PAP) is a rare disease characterized by the accumulation of surfactant components in alveoli, impairing gas exchange. The mainstay of treatment remains whole lung lavage (WLL); however, selected lobar lavage (SLL) using smaller volumes of normal saline has also been described. Due to the marked variability in the severity and natural history of PAP, there is a need for more tailored treatment approaches.METHODS Repeated outpatient SLL were performed using conscious sedation and fiberoptic bronchoscopy at intervals between 1 and 6 weeks. Each procedure targeted a single lobe, with the order of lavages based on degree of radiographic involvement. The bronchoscope was modified with a flushing pump to deliver warm normal saline in 100 mL aliquots up to a maximum of 3000 mL. Computed tomography scans and pulmonary function testing were performed at baseline and repeated after completion of all lavages.RESULTS Radiographic and symptomatic improvement was noted in all cases and physiologic improvement was noted in three of four cases. The only complication was transient procedural hypoxemia. All patients were able to be discharged home on the same day of their procedure.INTERPRETATION Our experience suggests outpatient SLL is a safe and effective alternative to WLL in mild-moderate cases of PAP with the benefits of avoiding admission to hospital, general anesthesia, and endotracheal intubation with single-lung ventilation. All patients remained relapse free for a minimum follow-up duration of 11 months.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".