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Record W4210267381 · doi:10.3389/fped.2021.833205

PCRRT Expert Committee ICONIC Position Paper on Prescribing Kidney Replacement Therapy in Critically Sick Children With Acute Liver Failure

2022· article· en· W4210267381 on OpenAlexaff
Rupesh Raina, Sidharth Kumar Sethi, Guido Filler, Shina Menon, Aliza Mittal, Amrit Khooblall, Prajit Khooblall, Ronith Chakraborty, Harsha Adnani, Nina Vijayvargiya, Sharon Teo, Girish Chandra Bhatt, Lee Jin Koh, Chebl Mourani, Marcelo de Sousa Tavares, Khalid Alhasan, Michael L. Forbes, Maninder Dhaliwal, Veena Raghunathan, Dieter C. Bröering, Azmeri Sultana, Giovanni Montini, Patrick D. Brophy, Mignon McCulloch, Timothy E. Bunchman, Hui‐Kim Yap, Rezan Topalglu, María Ferris

Bibliographic record

VenueFrontiers in Pediatrics · 2022
Typearticle
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineAcute kidney injuryDialysisRenal replacement therapyIntensive care medicineHepatorenal syndromeIncidence (geometry)Kidney diseaseRenal functionCirrhosisInternal medicine

Abstract

fetched live from OpenAlex

Management of acute liver failure (ALF) and acute on chronic liver failure (ACLF) in the pediatric population can be challenging. Kidney manifestations of liver failure, such as hepatorenal syndrome (HRS) and acute kidney injury (AKI), are increasingly prevalent and may portend a poor prognosis. The overall incidence of AKI in children with ALF has not been well-established, partially due to the difficulty of precisely estimating kidney function in these patients. The true incidence of AKI in pediatric patients may still be underestimated due to decreased creatinine production in patients with advanced liver dysfunction and those with critical conditions including shock and cardiovascular compromise with poor kidney perfusion. Current treatment for kidney dysfunction secondary to liver failure include conservative management, intravenous fluids, and kidney replacement therapy (KRT). Despite the paucity of evidence-based recommendations concerning the application of KRT in children with kidney dysfunction in the setting of ALF, expert clinical opinions have been evaluated regarding the optimal modalities and timing of KRT, dialysis/replacement solutions, blood and dialysate flow rates and dialysis dose, and anticoagulation methods.

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 score0.053
Threshold uncertainty score0.650

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 head0.008
GPT teacher head0.225
Teacher spread0.218 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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