1738. Incidence and Outcomes of Hospitalization with Invasive Fungal Infection Among Solid-Organ Transplant Recipients: A Population-Based Cohort Study
Bibliographic record
Abstract
Abstract Background Invasive fungal infection (IFI) in solid-organ transplant (SOT) recipients is associated with significant morbidity and mortality. The long-term probability of post-transplant IFI is poorly understood. Methods We conducted a population-based cohort study using linked administrative healthcare databases from Ontario, Canada to determine the incidence rate, 1-, 5- and 10-year cumulative probability of IFI-related hospitalization, and 1-year post-IFI all-cause mortality in SOT recipients from 2002 to 2016. We also examined post-IFI death-censored graft failure in renal transplant patients. Results We included 9326 SOT recipients (median follow-up 5.35 years). Overall, the incidence of IFI was 8.3 per 1000 person-years (95% confidence interval [CI]: 7.5–9.1). The 1-year cumulative probability of IFI was 7.4% (95% CI: 5.8–9.3%), 5.4% (95% CI: 3.6–8.1%), 1.8% (95% CI: 1.3–2.5%), 1.2% (95% CI: 0.5–3.2%), and 1.1% (95% CI: 0.9–1.4%) for lung, heart, liver, kidney-pancreas, and kidney-only transplant recipients, respectively. Lung transplant recipients had both the highest incidence rate and the highest 10-year probability of IFI: 43.0 per 1,000 person-years (95% CI: 36.8–50.0) and 26.4% (95% CI: 22.4–30.9%), respectively. Lung transplantation was also associated with the highest 1-year cumulative probability of post-IFI all-cause mortality (40.2%,95% CI: 33.1–48.3%). Among kidney transplant recipients, the 1-year probability of death-censored graft failure after IFI was 9.8% (95% CI: 6.0–15.8%). Conclusion The 1-year cumulative probability of IFI varies widely among SOT recipients. Lung transplantation was associated with the highest incidence of IFI with considerable 1-year all-cause mortality. The findings of this study considerably improved our understanding of the long-term probability of post-transplant IFI. Disclosures All authors: No reported disclosures.
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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 | 0.001 |
| 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".