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Record W4377940346 · doi:10.1111/liv.15622

Organ dysfunction and failure in liver disease

2023· review· en· W4377940346 on OpenAlexaff
Adrià Juanola, Neha Tiwari, Cristina Solé, Danielle Adebayo, Florence Wong, Pere Ginès

Bibliographic record

VenueLiver International · 2023
Typereview
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsUniversity of Toronto
FundersInstituto de Salud Carlos IIIHorizon 2020 Framework Programme
KeywordsMedicineCirrhosisLiver transplantationDiseaseLiver diseaseAlcoholic hepatitisOrgan dysfunctionHepatitisGastroenterologyIntensive care medicineAlcoholic liver diseaseSepsisInternal medicineTransplantation

Abstract

fetched live from OpenAlex

Acute-on-chronic liver failure (ACLF) is a complex syndrome defined by the existence of different organ failures (OFs) in patients with chronic liver disease, mainly cirrhosis. Several definitions have been proposed to define the syndrome, varying in the grade of the subjacent liver disease, the type of precipitants and the organs considered in the definition. Liver, coagulation, brain, kidney, circulatory and pulmonary are the six types of OFs proposed in the different classifications, with different prevalence worldwide. Irrespective of the definition used, patients who develop ACLF present a hyperactive immune system, profound haemodynamic disturbances and several metabolic alterations that finally lead to organ dysfunction. These disturbances are triggered by different factors such as bacterial infections, alcoholic hepatitis, gastrointestinal bleeding or hepatitis B virus flare, among others. Because patients with ACLF present high short-term mortality, a prompt recognition is needed to start treatment of the trigger event and specific organ support. Liver transplantation is also feasible in carefully selected patients and should be evaluated.

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 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 score0.905
Threshold uncertainty score0.699

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.050
GPT teacher head0.322
Teacher spread0.272 · 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

Citations9
Published2023
Admission routes1
Has abstractyes

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