Outcomes of liver transplantation for patients with alagille syndrome: The studies of pediatric liver transplantation experience
Bibliographic record
Abstract
Alagille syndrome (ALGS) is a multisystem disorder that manifests as childhood cholestasis. Reports of liver transplantation (LT) for patients with ALGS have come largely from single centers, which have reported survival rates of 57% to 79%. The aim of this study was to determine LT outcomes for patients with ALGS. We performed a retrospective analysis of the Studies of Pediatric Liver Transplantation database, which contains information about 3153 pediatric LT recipients. Data were available for 91 patients with ALGS and for 236 age-matched patients with biliary atresia (BA). The frequency of complex cardiac anomalies was lower in the LT group with ALGS versus published ALGS series (5% versus 13%). The pretransplant glomerular filtration rate (GFR) was <90 mL/minute/1.73 m(2) in 18% of the LT patients with ALGS and in 5% of the LT patients with BA (P < 0.001). The height deficit at listing was worse for the ALGS patients (66%) versus the BA patients (22%). The 1-year patient survival rates were 87% for the ALGS patients and 96% for the BA patients (P = 0.002). The deaths in the ALGS group mostly occurred within the first 30 days. No pretransplant factors associated with death were identified in the ALGS group. A survival analysis revealed that biliary (P = 0.02), vascular (P < 0.001), central nervous system (CNS; P < 0.001), and renal complications (P < 0.001) after LT were associated with death in the ALGS group. Renal insufficiency in the ALGS patients worsened after LT, and at 1 year, GFR was <90 mL/minute/1.73 m(2) in 22% of the LT patients with ALGS but in only 8% of the patients with BA (P = 0.0014). More LT pediatric patients with ALGS either were currently receiving special education (50% versus 30% for BA patients, P = 0.02) or had received special education in the past (60% versus 36%, P = 0.01). Vascular, CNS, and renal complications were increased in the ALGS patients after LT, and this reflected multisystem involvement. Although the 1-year survival rate was modestly lower for the ALGS patients versus the BA patients, the clustering of deaths within the first 30 days is notable and warrants increased vigilance and further investigation.
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".