MétaCan
Menu
Back to cohort
Record W2911925858 · doi:10.1097/mpg.0000000000002283

Similarities and Differences in Allocation Policies for Pediatric Liver Transplantation Across the World

2019· article· en· W2911925858 on OpenAlexaff
Björn Fischler, Ulrich Baumann, Daniel D’Agostino, Lorenzo D’Antiga, Antal Dezsőfi, Dominique Debray, Özlem Durmaz, Helen Evans, E. Frauca, Nedim Hadžić, Jörg Jahnel, Jerome Loveland, Valérie A. McLin, Vicky L. Ng, Valério Nobili, Joanna Pawłowska, Khalid Sharif, Françoise Smets, Henkjan J. Verkade, Evelyn Hsu, Simon Horslen, John C. Bucuvalas

Bibliographic record

VenueJournal of Pediatric Gastroenterology and Nutrition · 2019
Typearticle
Languageen
FieldMedicine
TopicOrgan Transplantation Techniques and Outcomes
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineHepatologyLiver transplantationDonationTransplantationWaiting listOrgan donationFamily medicinePediatric gastroenterologyPediatricsInternal medicineDemography

Abstract

fetched live from OpenAlex

OBJECTIVES: We aimed to investigate national allocation policies for pediatric liver transplantation (LT). METHOD: A survey was prepared by the European Society for Paediatric Gastroenterology Hepatology and Nutrition Hepatology Committee in collaboration with the North American Studies of Pediatric Liver Transplantation consortium. The survey was sent to pediatric hepatologists and transplant surgeons worldwide. National data were obtained from centrally based registries. RESULTS: Replies were obtained from 15 countries from 5 of the world continents. Overall donation rate varied between 9 and 35 per million inhabitants. The number of pediatric LTs was 4 to 9 per million inhabitants younger than 18 years for 13 of the 15 respondents. In children younger than 2 years mortality on the waiting list (WL) varied between 0 and 20%. In the same age group, there were large differences in the ratio of living donor LT to deceased donor LT and in the ratio of split liver segments to whole liver. These differences were associated with possible discrepancies in WL mortality. CONCLUSIONS: Similarities but also differences between countries were detected. The described data may be of importance when trying to reduce WL mortality in the youngest children.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.050
Threshold uncertainty score0.222

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)0.0000.000

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 head0.014
GPT teacher head0.274
Teacher spread0.260 · 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 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

Citations20
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Pediatric Gastroenterology and NutritionSame topicOrgan Transplantation Techniques and OutcomesFrench-language works237,207