Surveillance bronchoscopy in cystic fibrosis transplanted patients is safe and effective
Bibliographic record
Abstract
Introduction: Acute cellular rejection (ACR) and infection are significant causes of morbidity and mortality in transplanted recipients. The use of scheduled post-transplant biopsies (SPB) remains controversial because of its risk-benefit ratio compared to biopsies on clinical demand. Cystic fibrosis (CF) recipients have a higher risk of early immunological complications (ACR and antibody mediated rejection) compared to other diseases. Few studies have evaluated the effectiveness and safety of SPB in CF, with special regard to the time period elapsed from lung transplantation (LTx). Aim: To investigate the incidence of ACR and microbial infection in CF recipients, the safety and adequacy of SPB in detecting ACR and whether the time after LTx may influence these results. Methods: A single-centre retrospective analysis was performed on CF patients who underwent SPB for LTx between January 2019 and December 2020. The time after LTx was recorded in each patient. Results: 92 SPB were performed with a median time after LTx of 24 months (range 1-148). 89(97%) had adequate samples, and ACR was diagnosed in 13 procedures (11%). 3(3.2%) pneumothorax and 3(3.2%) major bleeding were reported. ACR and complication incidence were similar when considering the different time period elapsed from LTx (0-1, 1-2, 2-3, 3-4 and >4 years). CF transplanted from >2 years had a significantly higher number of ACR that required treatment [8/8(100%) vs 2/5(46%), p=0.03] and a lower incidence of infections [5/46(11%) vs 14/46(30%), p=0.03] than those transplanted <2 years. Conclusions: In CF recipients, SPB is a safe and accurate procedure to identify ACR that should be routinely performed in transplant recipient follow-up.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".