Renal anomalies in Alagille syndrome: A disease‐defining feature
Bibliographic record
Abstract
Alagille syndrome (ALGS) is an autosomal dominant condition, primarily caused by mutations in JAGGED1. ALGS is defined by cholestatic liver disease, cardiac disease and involvement of the face, skeleton, and eyes with variable expression of these features. Renal involvement has been reported though not formally described. The objective of this study was to systematically characterize the renal involvement in ALGS. We performed a retrospective review of 466 JAGGED1 mutation-positive ALGS patients. Charts were reviewed for serum biochemistries, renal ultrasounds or other imaging, urinalysis, and clinical reports from pediatric nephrologists. The clinical data were reviewed by two pediatric hepatologists and a pediatric nephrologist. Of 466 charts reviewed we found 187 yielded evaluable renal information. Of these, 73/187 were shown to have renal involvement, representing 39% of the study cohort. Renal dysplasia was the most common anomaly seen. Genotype analysis of the JAGGED1 mutations in the patients with and without renal involvement did not reveal an association with mutation type. From the study we concluded that renal involvement has a prevalence of 39% in ALGS in our evaluable patients. Renal dysplasia is the most common renal anomaly. This finding correlates with the known role of the Notch pathway in glomerular development. Since renal disease of the type seen in ALGS can impair growth and impact liver transplantation, there is a clear need for a prospective study of renal involvement in ALGS and the development of guidelines for evaluation and management. These data also suggest that renal involvement be considered the sixth defining criterion for ALGS.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".