MétaCan
Menu
Back to cohort
Record W2565339423 · doi:10.3350/cmh.2016.0056

Acute kidney injury in liver cirrhosis: new definition and application

2016· review· en· W2565339423 on OpenAlexaff
Florence Wong

Bibliographic record

VenueClinical and Molecular Hepatology · 2016
Typereview
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHepatorenal syndromeMedicineAcute kidney injuryCirrhosisAscitesCreatinineInternal medicineGastroenterologyStage (stratigraphy)Intensive care medicine

Abstract

fetched live from OpenAlex

The traditional diagnostic criteria of renal dysfunction in cirrhosis are a 50% increase in serum creatinine (SCr) with a final value above 1.5 mg/dL. This means that patients with milder degrees of renal dysfunction are not being diagnosed, and therefore not offered timely treatment. The International Ascites Club in 2015 adapted the term acute kidney injury (AKI) to represent acute renal dysfunction in cirrhosis, and defined it by an increase in SCr of 0.3 mg/dL (26.4 µmoL/L) in <48 hours, or a 50% increase in SCr from a baseline within ≤3 months. The severity of AKI is described by stages, with stage 1 represented by these minimal changes, while stages 2 and 3 AKI by 2-fold and 3-fold increases in SCr respectively. Hepatorenal syndrome (HRS), renamed AKI-HRS, is defined by stage 2 or 3 AKI that fulfils all other diagnostic criteria of HRS. Various studies in the past few years have indicated that these new diagnostic criteria are valid in the prediction of prognosis for patients with cirrhosis and AKI. The future in AKI diagnosis may include further refinements such as inclusion of biomarkers that can identify susceptibility for AKI, differentiating the various prototypes of AKI, or track its progression.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.083
GPT teacher head0.440
Teacher spread0.357 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations81
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueClinical and Molecular HepatologySame topicAcute Kidney Injury ResearchFrench-language works237,207