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Record W2908641968 · doi:10.1055/s-0038-1676805

Child–Pugh Classification: Time to Abandon?

2019· review· en· W2908641968 on OpenAlexaff
Beverley Kok, Juan G. Abraldeṣ

Bibliographic record

VenueSeminars in Liver Disease · 2019
Typereview
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTransjugular intrahepatic portosystemic shuntCirrhosisHepatocellular carcinomaMedicineContext (archaeology)Intensive care medicinePortal hypertensionInternal medicine

Abstract

fetched live from OpenAlex

The Child-Pugh classification is one of the commonest and oldest bedside tools utilized in estimating prognosis in patients with cirrhosis. However, its usage as a risk prediction tool or indeed a decision-making tool should be revisited. In this review, we discuss some inherent issues with the Child-Pugh classification and present a few contexts in which the current usage of Child-Pugh warrants reassessment, elaborating on its utility in acute variceal bleeding, specifically its role in decision-making on early transjugular intrahepatic portosystemic shunt, as well as its use in the context of hepatocellular carcinoma and drug development and dose adjustment.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0000.002
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.039
GPT teacher head0.322
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), 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

Citations110
Published2019
Admission routes1
Has abstractyes

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