Long-term outcomes of sensitized lung transplant recipients after peri-operative desensitization
Bibliographic record
Abstract
The Toronto Lung Transplant Program has been using a peri-operative desensitization regimen of plasma exchange, intravenous immune globulin, and antithymocyte globulin in order to accept donor-specific antibody (DSA)-positive lung transplants safely since 2008. There are no long-term data on the impact of this practice on allograft survival or the development of chronic lung allograft dysfunction (CLAD). We extended our prior study to include long-term follow-up of 340 patients who received lung transplants between January 1, 2008 and December 31, 2011. We compared allograft survival and CLAD-free survival among patients in three cohorts: DSA-positive, panel reactive antibody (PRA)-positive/DSA-negative, and unsensitized at the time of transplant. The median follow-up time in this extension study was 6.7 years. Among DSA-positive, PRA-positive/DSA-negative, and unsensitized patients, the median allograft survival was 8.4, 7.9, and 5.8 years, respectively (p = .5908), and the median CLAD-free survival was 6.8, 7.3, and 5.7 years, respectively (p = .5448). This follow-up study confirms that long-term allograft survival and CLAD-free survival of patients who undergo DSA-positive lung transplants with the use of our protocol do not differ from other lung transplant recipients. Use of protocols such as ours, therefore, may improve access to transplant for sensitized candidates.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".