Lung Transplantation in Systemic Sclerosis: a Practice Survey of United States Lung Transplant Centers
Bibliographic record
Abstract
Lung transplantation in patients with systemic sclerosis (SSc) can be complicated by extrapulmonary manifestations of the disease, leading to concerns regarding posttransplant complications and outcomes. METHODS: We conducted a web-based survey of adult lung transplant programs in the United States regarding their practices in patients with SSc. RESULTS: Sixty percent (37/62) of the eligible centers responded to the survey, majority of the respondents were medical directors (81%). Most centers would consider transplanting patients with mild or moderate esophageal disease (92% or 75%, respectively) or gastroparesis (59%). A minority would consider patients with severe esophageal dysmotility (37%), digital ulcers (21%), or low body mass index (19%). Most centers conducted extensive pretransplant gastrointestinal evaluation and use a conservative feeding approach with prolonged nothing by mouth (83%) and postpyloric feeding (89%). Antireflux surgery is commonly considered (40%) with partial fundoplication being the procedure of choice (67%). Most respondents expected similar outcomes of acute or chronic rejection (81% and 51%, respectively), respiratory infections (76%), and 1-year survival (70%). CONCLUSIONS: Most US lung transplant centers do not universally exclude SSc from lung transplant listing, but most support extensive pretransplant gastrointestinal testing and a conservative approach to feeding in the early posttransplant period.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".