Echinocandin use in lung transplant recipients
Bibliographic record
Abstract
BACKGROUND: Invasive fungal infections (IFI) are associated with significant morbidity and mortality in lung transplant recipients (LTRs). However, data outlining use of echinocandins in prophylaxis and therapy of LTRs are limited. METHOD: A single-center retrospective cohort study on all LTRs from January-2010 to December-2016. Participants were screened for antifungal use to assess rate, tolerability, and clinical outcome of echinocandin use in LTRs, during the first 6 weeks of posttransplant. RESULTS: A total of 777 lung transplants were reviewed in 763 LTRs. Antifungals were administered to 268 (35%) of LTRs. Reasons included preemptive antifungal therapy (55% [149/268]), targeted antifungal prophylaxis (34% [92/268]), and definitive IFI therapy (10% [27/268]). Azoles were first-line agents in 80% (215/268) of LTRs, caspofungin in 11% (30/268), micafungin in 6.7% (18/268), amphotericin B in 1.5% (4/268), and anidulafungin in 0.4% (1/268]). LTRs were started on echinocandins due to abnormal liver enzymes in 91% (46/49). Overall, 23% (50/215) of LTR's were switched off azoles. Of these, 54% (27/50) were switched to echinocandins. Switch from azoles to echinocandin was undertaken due to abnormal liver enzymes in 63% (17/27). No patients receiving first-line echinocandins were switched to other therapies due to adverse events. CONCLUSIONS: Our data suggest that echinocandins are utilized in approximately 18.3% of lung transplant recipients. They are the preferred second-line agents due to a lower adverse-effect profile compared to the azoles.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".