Lung Transplantation From Donors With a History of Substance Use
Bibliographic record
Abstract
BACKGROUND: Substance use is common among lung transplant donors, but concerns persist about graft damage. Stimulant drugs such as cocaine and methamphetamine can induce pulmonary arterial hypertension, while smoked products such as cannabis and crack cocaine can produce airway and parenchymal diseases. We sought to characterize donor substance use at our center and evaluate the associations with recipient survival as well as chronic lung allograft dysfunction (CLAD), severe primary graft dysfunction (PGD3), and baseline lung allograft dysfunction (BLAD). METHODS: We studied patients with double lung transplants in our program between 2004 and 2016, including a history of donor substance use with nine pre-specified agents. We modeled the association with time to death or retransplant, CLAD, severe PGD, and BLAD. RESULTS: Of 473 recipients, 186 (39%) received lungs from a donor with a history of substance use with at least one of the pre-specified substances. There was no overall relationship between donor substance use and any outcome. Heavy donor smoking was associated with an increased risk of death or retransplant (hazard ratio 1.47; p = 0.032), PGD3 (odds ratio [OR]: 2.13; p = 0.014), and BLAD (OR 2.56; p < 0.001). Donor crack cocaine use (n = 24) was also associated with worse survival (HR 2.16; 95% CI 1.16-3.66; p = 0.017) but not CLAD or BLAD. We noted no CLAD associations with any drug. CONCLUSION: A history of donor substance use was common and in general not associated with worse outcomes, aside from heavy donor smoking. These findings may have implications for allocation and post-transplant graft dysfunction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".