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Record W2985991419 · doi:10.5546/aap.2017.eng.385

Management of cirrhotic ascites in children. Review and recommendations. Part 1: Pathophysiology, diagnostic evaluation, hospitalization criteria, treatment, nutritional management

2017· review· en· W2985991419 on OpenAlexaff
David Bes, María C. Martín Fernández, Ivone Malla, Horacio A. Repetto, Daniel Buamsch, Susana López, Roxana Martinitto, Miriam Cuarterolo, Fernando Álvarez

Bibliographic record

VenueArchivos Argentinos de Pediatria · 2017
Typereview
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineAscitesSpontaneous bacterial peritonitisParacentesisCirrhosisHyponatremiaIntensive care medicinePathophysiologyGynecologySurgeryGastroenterologyInternal medicine

Abstract

fetched live from OpenAlex

Ascites is a major complication of cirrhosis. There are several evidence-based articles and guidelines for the management of adults, but few data have been published in relation to children. In the case of pediatric patients with cirrhotic ascites (PPCA), the following questions are raised: How are the clinical assessment and ancillary tests performed? When is ascites considered refractory? How is it treated? Should fresh plasma and platelets be infused before abdominal paracentesis to prevent bleeding? What are the hospitalization criteria? What are the indicated treatments? What complications can patients develop? When and how should hyponatremia be treated? What are the diagnostic criteria for spontaneous bacterial peritonitis? How is it treated? What is hepatorenal syndrome? How is it treated? When should albumin be infused? When should fluid intake be restricted? The recommendations made here are based on pathophysiology and suggest the preferred approach to its diagnostic and therapeutic aspects, and preventive care.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.055
GPT teacher head0.382
Teacher spread0.327 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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