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Record W4391813026 · doi:10.1097/mog.0000000000001016

Terlipressin for hepatorenal syndrome

2024· article· en· W4391813026 on OpenAlexaff
Florence Wong

Bibliographic record

VenueCurrent Opinion in Gastroenterology · 2024
Typearticle
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsToronto General HospitalUniversity of Toronto
Fundersnot available
KeywordsTerlipressinHepatorenal syndromeMedicineInternal medicineCirrhosis

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The definition and diagnostic criteria of hepatorenal syndrome-acute kidney injury (HRS-AKI) has undergone recent changes. A major vasoconstrictor, terlipressin, has recently been approved as pharmacotherapy for HRS-AKI in the United States. The purpose of this review is to familiarize the readers with these new diagnostic criteria of HRS-AKI, and how best to use terlipressin. RECENT FINDINGS: Terlipressin is effective either as bolus dosing or continuous infusion and can achieve reversal of HRS-AKI in approximately 40% of patients. Continuous infusion allows lower daily dose with equal efficacy and less side effects but not an approved mode of administration in the United States. Response to terlipressin in the randomized controlled trials was defined as repeat reduction of serum creatinine to less than 1.5 mg/dl. Newer studies will likely require response to treatment to be defined as a repeat serum creatinine to be less than 0.3 mg/dl from baseline. Terlipressin use is associated with ischemic side effects and potential for respiratory failure development. SUMMARY: Careful patient selection and close monitoring are necessary for its use. Response to terlipressin with HRS-AKI reversal is associated with improved outcomes with better survival and less requirement for renal replacement therapy.

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 score0.016
Threshold uncertainty score0.336

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 head0.044
GPT teacher head0.359
Teacher spread0.315 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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