IBAT inhibitors in pediatric cholestatic liver diseases: Transformation on the horizon?
Bibliographic record
Abstract
Historically, the therapeutic options available to hepatologists managing cholestasis have been limited. Apart from bile acid--binding resins and the choleretic ursodeoxycholic acid, the medical management of cholestasis in children has been predominately focused on managing the complications of cholestasis, namely pruritus, malnutrition, fat-soluble vitamin deficiencies, and portal hypertension. As such, invasive surgical procedures such as biliary diversion and liver transplantation may become the only options for progressive and unremitting cases of cholestasis. Particularly in the pediatric population, where debilitating pruritus is a common indication for a liver transplant, effective anti-cholestatic medications have the potential to prolong native liver survival without the need for biliary diversion. Ileal bile acid transporter (IBAT) inhibitors are a relatively new class of drugs which that target the ileal re-uptake of bile acids, thus interrupting the enterohepatic circulation and reducing the total bile acid pool size and exposure of the liver. Oral, minimally absorbed IBAT inhibitors have been demonstrated to reduce serum bile acid levels and pruritus with a minimal side effect profile in clinical trials in Alagille Ssyndrome and progressive familial intrahepatic cholestasis, leading to FDA and EMA approval. The indications for IBAT inhibitors will likely expand in the coming years as clinical trials in other adult and pediatric cholestatic conditions are ongoing. This review will summarize the published clinical and pre-clinical data on IBAT inhibitors and offer providers guidance on their practical use.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".