Pathophysiology, epidemiology, classification and treatment options for polycystic liver diseases
Bibliographic record
Abstract
Polycystic liver diseases (PLD) represent a group of genetic disorders in which cysts occur in the liver (autosomal dominant polycystic liver disease) or in combination with cysts in the kidneys (autosomal dominant polycystic kidney disease). Regardless of the genetic mutations, the natural history of these disorders is alike. The natural history of PLD is characterized by a continuous increase in the volume and the number of cysts. Both genders are affected; however, women have a higher prevalence. Most patients with PLD are asymptomatic and can be managed conservatively. Severe symptoms can affect 20% of patients who develop massive hepatomegaly with compression of the surrounding organs. Rrarely, patients with PLD suffer from acute complications caused by the torsion of hepatic cysts, intraluminal cystic hemorrhage and infections. The most common methods for the diagnosis of PLD are cross sectional imaging studies. Abdominal ultrasound and computerized tomography are the two most frequently used investigations. Magnetic resonance imaging is more sensitive and specific, and it is a valuable test for patients with intravenous contrast allergies or renal dysfunction. Different treatment modalities are available to physicians caring for these patients. Medical treatment has been ineffective. Percutaneous sclerotherapy, trans-arterial embolization, cyst fenestration, hepatic resection and liver transplantation are indicated to specific groups of patients and have to be tailored according to the extent of disease. This review outlines the current knowledge of the pathophysiology, clinical course, diagnosis and treatment strategies of PLD.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".