Diagnosis and management of acute kidney injury in patients with cirrhosis: revised consensus recommendations of the International Club of Ascites
Bibliographic record
Abstract
Acute renal failure (ARF) is a common complication in patients with decompensated cirrhosis. The traditional diagnostic criteria of renal failure in these patients were proposed in 1996 and have been refined in subsequent years. According to these criteria, ARF is defined as an increase in serum creatinine (sCr) of >/= 50% from baseline to a final value >1.5 mg/dl (133 umol/L). However, the threshold value of 1.5 mg/dl (133umol/L) sCr to define renal failure in patients with decompensated cirrhosis has been challenged. In addition, the timeframe to distinguish acute from chronic renal failure has not been clearly identified, the only exception being type 1 hepatorenal syndrome (HRS). Meanwhile, new definitions for ARF, now termed acute kidney injury (AKI), have been proposed and validated in patients without cirrhosis. Recently these new criteria were also proposed and applied in the diagnosis of AKI in patients with cirrhosis. Thus, in December 2012, the International Club of Ascites (ICA) organised a consensus development meeting in Venice, Italy, in order to reach a new definition of AKI in patients with cirrhosis. The discussion among the experts continued thereafter for 2 years, both online and through several meetings, between those experts who had different positions on crucial points on the subject. This paper reports the scientific evidence supporting the final proposal of a new approach to the diagnosis and treatment of this condition, on which the experts agreed.
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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 | 0.054 | 0.060 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.007 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.001 | 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".