Abstract 18474: Risk Factors for Long Term Morbidity After Pediatric Heart Retransplantation : Analysis from the International Society of Heart and Lung Transplantation Registry
Bibliographic record
Abstract
Recent detailed analysis of the ISHLT registry has shown that retransplantation [ReTx] following pediatric primary heart transplantation [PTx] has inferior outcomes. Little is known about long-term morbidities following ReTx. Data from the ISHLT registry (1998-2010) were used to examine risk factors for long-term morbidities in all ReTx patients with a PTx at age < 18 y. 9,966 transplants were reviewed: 9,248 PTx, 602 first ReTx and 32 second ReTx. Long term morbidities were significantly (p<0.001) more common after ReTx than PTx including allograft vasculopathy [AV] (HR 2.8), late rejection (HR 2.0) and late renal dysfunction (HR 2.6); but not PTLD (HR 1.2, p=0.52). Factors associated with development of AV after ReTx included history of hypertension [HTN] pre-ReTx (HR 1.8, p=0.003), AV as the indication for ReTx (HR 1.96, p=0.003) , donor factors including HTN (HR 5.7, p=0.001) , diabetes (HR 5.7, p=0.005), cocaine use (HR 2.6, p=0.02), male donor to female recipient (HR 1.5, p=0.02); and post-ReTx factors including renal dysfunction (HR 1.8, p=0.002), hospitalization for infection (HR 2.7, p=0.04) and drug treated HTN (HR 1.6, p=0.05). Risk for late rejection after ReTx included CMV+ serology pre-ReTx (HR 1.7, p=0.03), donor CMV+ serology (HR 1.8, p=0.007), early rejection post-ReTx (HR 1.6, p=0.03), documented non-compliance (HR 3.6, p<0.001), and later year of ReTx (HR 1.3, p<0.001). Risk factors for late renal dysfunction included higher pre-ReTx creatinine (HR 1.3, p<0.001), later year of ReTx (HR 1.1, p<0.001), dialysis post-ReTx (HR 4.0, p<0.001), drug treated HTN in follow-up (HR 3.4, p<0.001), development of AV (HR 1.7, p=0.003) and hospitalization for infection (HR 4.1, p=0.008). In a multivariate model, no associations were found between duration of PTx (e.g. cumulative health burden) and any of the ReTx morbidities. ReTx following PTx in the pediatric age range is associated not only with inferior outcomes but also with a significant risk of long term morbidities. Further study of the key risk factors identified may help in patient and donor selection for ReTx with the goal to improve outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 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".