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Record W2098913448 · doi:10.1093/ndt/gfr736

Medical management of hepatorenal syndrome

2012· review· en· W2098913448 on OpenAlexfundno aff
Andrew Davenport, Jawad Ahmad, Ali Al‐Khafaji, John A. Kellum, Yuri Genyk, Mitra K. Nadim

Bibliographic record

VenueNephrology Dialysis Transplantation · 2012
Typereview
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsnot available
FundersUniversity of MelbourneUniversità degli Studi di PadovaChulalongkorn UniversityUniversity of TorontoUniversity College LondonOtsuka PharmaceuticalUniversità degli Studi di MilanoIkariaUniversity of PittsburghUniversity of AlbertaUniversity of WashingtonGeorge Washington UniversityUniversity of Southern California
KeywordsHepatorenal syndromeMedicineCirrhosisRenal functionLiver transplantationInternal medicineBlood pressureGastroenterologyLiver diseaseKidney diseaseTransplantationCardiologyIntensive care medicine

Abstract

fetched live from OpenAlex

Hepatorenal syndrome (HRS) is defined as the occurrence of renal dysfunction in a patient with end-stage liver cirrhosis in the absence of another identifiable cause of renal failure. The prognosis of HRS remains poor, with a median survival without liver transplantation of <6 months. However, understanding the pathogenesis of HRS has led to the introduction of treatments designed to increase renal perfusion and mean arterial blood pressure using vasopressors and albumin, which has led to improvement in renal function in ∼50% of patients.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.781
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.309
Teacher spread0.280 · 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.

Study designOther design
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

Citations40
Published2012
Admission routes1
Has abstractyes

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