Prospective Evaluation of the Prevalence and Clinical Significance of Positive Autoantibodies After Pediatric Liver Transplantation
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: De novo autoimmune hepatitis (AIH) recently was recognized as an important cause of late graft dysfunction after pediatric liver transplantation (LT). However, the significance of isolated elevation of autoantibodies in children after LT without history of prior autoimmune liver disease scarcely has been studied. The aim of the present study was to determine the prevalence and risk factors for autoantibodies production in pediatric LT recipients and to assess the impact of isolated elevation of autoantibodies over time on graft function. METHODS: Sixty-eight children without history of autoimmune disease were recruited over the course of 1 year into this cross-sectional study. A single blood specimen was drawn at study entry to determine titers of autoantibodies. Clinical and laboratory assessment and medical history were obtained at study entry as well. Patients were then divided into positive and negative autoantibodies groups, and prospectively followed for 18 months for evidence of abnormal liver function tests. RESULTS: One or more autoantibodies were detected in 18 (26%) patients. Anti-smooth muscle was the most common (n = 13) antibody. Time since transplant (>4 years) was the only risk factor identified for the presence of autoantibodies (univariate risk ratio, 3.3; 95% confidence interval, 1.2-9). During the follow-up period, 5 patients with positive autoantibody screen developed de novo AIH (n = 3) or chronic rejection (n = 2), compared with 0 in the negative autoantibody group. Children with positive autoantibody screen were at higher risk for development of de novo AIH or chronic rejection (univariate risk ratio 13.9; 95% confidence interval, 1.7-111; P = 0.004). CONCLUSIONS: Positive autoantibodies are common in children after LT and their presence may denote a higher risk for the development of de novo AIH or chronic rejection over time.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".