Abstract 14448: Graft Loss and Rejection Following COVID in Pediatric Heart Transplantation - A Pediatric Heart Transplant Society (PHTS) Propensity Matched Analysis
Bibliographic record
Abstract
Introduction: While short-term outcomes following COVID among pediatric heart transplant (HT) recipients have been described, graft outcomes including the risks of subsequent graft loss and rejection following COVID are unknown. Hypothesis: We sought to determine the overall trends of post-HT survival during the COVID pandemic and determine if there was an increased risk for subsequent graft loss and/or rejection following post-HT COVID. Methods: All pediatric recipients of first HT between 1/2003-6/2022 in the Pediatric Heart Transplant Society ( PHTS) database were included. To assess if early post-HT survival changed during the COVID pandemic, 2-year HT survival was compared among those who underwent HT in 2014-2016, 2017-2019, and 2020-2022. To compare the risks of graft loss and rejection (acute cellular and/or antibody-mediated) between those with vs without post-HT COVID, a 1:2 (COVID vs non-COVID) propensity-score matched analysis using multiple pre-HT and post-HT factors (including exact matches for HT year and time post-HT) and Kaplan Meir analysis were performed. Patients with COVID within 3 months post-HT were excluded. Results: The 2-year post-HT survival was similar among patients who underwent HT across the 3 eras (Fig 1A). Among the overall 6634 patients (n = 888 [13%] with post-HT COVID), 861 patients with post-HT COVID and 1716 without post-HT COVID were included in propensity-score matching. There was no difference in the risk of subsequent graft loss (Fig 1B) or rejection (Fig 1C) among those with vs those without post-HT COVID. Conclusions: No differences were observed in early pediatric post-HT survival during the COVID pandemic compared to the immediately prior era. Post-HT COVID did not increase the risks of subsequent graft loss or rejection. Longer-term follow up is necessary to look at other potential post-HT COVID outcomes, such as coronary allograft vasculopathy.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".