Review article: Recent advances in ascites and acute kidney injury management in cirrhosis
Bibliographic record
Abstract
BACKGROUND: Better understanding of disease pathophysiology has led to advances in managing ascites and its associated complications including hepatorenal syndrome-acute kidney Injury (HRS-AKI), especially medicinal and interventional advances. AIM: To review the latest changes in the management of ascites and HRS-AKI. METHODS: A literature search was conducted in Pubmed, using the keywords cirrhosis, ascites, renal dysfunction, acute kidney injury, hepatorenal syndrome, beta-blockers, albumin, TIPS and vasoconstrictors, including only publications in English. RESULTS: The medicinal advances include earlier treatment of clinically significant portal hypertension to delay the onset of ascites and the use of human albumin solution to attenuate systemic inflammation thus improving the haemodynamic changes associated with cirrhosis. Furthermore, new classes of drugs such as sodium glucose co-transporter 2 are being investigated for use in patients with cirrhosis and ascites. For HRS-AKI management, newer pharmacological agents such as vasopressin partial agonists and relaxin are being studied. Interventional advances include the refinement of TIPS technique and patient selection to improve outcomes in patients with refractory ascites. The development of the alfa pump system and the study of outcomes associated with the use of long-term palliative abdominal drain will also serve to improve the quality of life in patients with refractory ascites. CONCLUSIONS: New treatment strategies emerged from better understanding of the pathophysiology of ascites and HRS-AKI have shown improved prognosis in these patients. The future will see many of these approaches confirmed in large multi-centre clinical trials with the aim to benefit the patients with ascites and HRS-AKI.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".