Invasive fungal infections in pediatric heart transplant recipients: Incidence, risk factors, and outcomes
Bibliographic record
Abstract
There are limited data on the incidence or risk factors for IFI in pediatric heart transplant recipients. The purpose of this study was to describe the incidence and types of IFI, to determine risk factors for outcomes of IFI, and to assist in decision-making concerning the need for prophylactic strategies in pediatric heart transplant recipients. Data from a multi-institutional registry of 1854 patients transplanted between 01/93 and 12/04 were analyzed to determine risk factors and outcomes of children with IFI post-heart transplantation. One hundred and thirty-nine episodes of IFI occurred in 123 patients and made up 6.8% of the total number of post-transplant infections. IFI was most commonly attributed to yeast (66.2%), followed by mold (15.8%) and Pneumocystis jiroveci (13%). Ninety percent of the yeast infections were caused by Candida spp., and Aspergillus spp. was causative in 82% of the mold infections. There was a significantly increased risk of fungal infection associated with pretransplant invasive procedures (e.g., ECMO, prior surgery, VAD, mechanical ventilation) with an incremental risk with increasing numbers of invasive procedures (early phase 0 vs. 1, RR 1.3; 0 vs. 3, RR 2.3; p<0.001). In multivariate analysis, previous surgery (p=0.05) and mechanical support at transplantation (p=0.01) remained significant. Forty-nine percent of recipients with IFI died, all within six months post-transplant. Invasive fungal infections are uncommon in pediatric heart transplant recipients. Risk and mortality are highest in the first six months post-transplant especially in patients with previous surgery and those requiring mechanical support. Prophylactic strategies for high-risk patients should be considered and warrants further study.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".