Invasive aspergillosis in liver transplant recipients in the current era
Bibliographic record
Abstract
Invasive aspergillosis (IA) is a rare but fatal disease among liver transplant recipients (LiTRs). We performed a multicenter 1:2 case-control study comparing LiTRs diagnosed with proven/probable IA and controls with no invasive fungal infection. We included 62 IA cases and 124 matched controls. Disseminated infection occurred only in 8 cases (13%). Twelve-week all-cause mortality of IA was 37%. In multivariate analyses, systemic antibiotic usage (adjusted odds ratio [aOR], 4.74; P = .03) and history of pneumonia (aOR, 48.7; P = .01) were identified as independent risk factors associated with the occurrence of IA. Moreover, reoperation (aOR, 5.99; P = .01), systemic antibiotic usage (aOR, 5.03; P = .04), and antimold prophylaxis (aOR, 11.9; P = .02) were identified as independent risk factors associated with the occurrence of early IA. Among IA cases, Aspergillus colonization (adjusted hazard ratio [aHR], 86.9; P < .001), intensive care unit stay (aHR, 3.67; P = .02), disseminated IA (aHR, 8.98; P < .001), and dialysis (aHR, 2.93; P = .001) were identified as independent risk factors associated with 12-week all-cause mortality, while recent receipt of tacrolimus (aHR, 0.11; P = .001) was protective. Mortality among LiTRs with IA remains high in the current era. The identified risk factors and protective factors may be useful for establishing robust targeted antimold prophylactic and appropriate treatment strategies against IA.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".