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Record W2163516510 · doi:10.1111/ans.12522

Kasai hepatoportoenterostomy in <scp>S</scp>outh <scp>A</scp>ustralia: a case for ‘centralized decentralization’

2014· article· en· W2163516510 on OpenAlexaboutno aff
Chen Gang Tu, Sanjeev Khurana, Richard Couper, Andrew W. D. Ford

Bibliographic record

VenueANZ Journal of Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicPediatric Hepatobiliary Diseases and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBiliary atresiaJaundiceChild survivalSurvival analysisLiver transplantationSurvival rateOverall survivalDecentralizationPopulationIncidence (geometry)Internal medicineDemographySurgeryTransplantationHealth servicesEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Recent follow-up studies have demonstrated significant improvement in overall survival as well as survival with native liver following geographic centralization of services to three centres in the UK. However, this model has not been replicated in countries with relatively low population density such as Australia and Canada. METHODS: Retrospective evaluation of all patients born with biliary atresia (BA) in South Australia from 1989 to 2010 was performed. Thirty-one patients with BA were discovered. Two patients were excluded because the initial Kasai procedure (KP) was performed interstate. Outcome parameters measured were (i) clearance of jaundice (bilirubin of less than 20 μmol/L, by 6 months); (ii) survival with native liver; and (iii) overall survival. Kaplan-Meier survival curves were plotted for both survival with native liver and overall survival. RESULTS: The incidence of BA in South Australia between 1989 and 2010 was 7.48 per 100,000 live births. Following KP, clearance of jaundice was achieved in 42.9% of patients. Five-year actuarial survival with native liver was 55.2%, and overall 5-year actuarial survival was 89.3%. CONCLUSIONS: The results of KP performed at Women's and Children's Hospital from 1989 to 2010 can be considered comparable with international benchmarks. Based on these results, we propose the creation of a 'centralized' pool of surgeons in Australia to help continue providing 'decentralized' care of BA.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.034
GPT teacher head0.285
Teacher spread0.251 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations12
Published2014
Admission routes1
Has abstractyes

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