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Record W4391323902 · doi:10.1371/journal.pone.0296690

Comparative efficacy of terlipressin and norepinephrine for treatment of hepatorenal syndrome-acute kidney injury: A systematic review and meta-analysis

2024· review· en· W4391323902 on OpenAlexfundno aff
Jody C. Olson, Ram Subramanian

Bibliographic record

VenuePLoS ONE · 2024
Typereview
Languageen
FieldMedicine
TopicLiver Disease and Transplantation
Canadian institutionsnot available
FundersMallinckrodt Pharmaceuticals
KeywordsTerlipressinHepatorenal syndromeMedicineInternal medicineAcute kidney injuryMeta-analysisRandomized controlled trialClinical endpointPlaceboIntensive care medicineCirrhosisPathology

Abstract

fetched live from OpenAlex

The treatment of choice for hepatorenal syndrome-acute kidney injury (HRS-AKI) is vasoconstrictor therapy in combination with albumin, preferably norepinephrine or terlipressin as recommended by recent guidelines. In the absence of larger head-to-head trials comparing the efficacy of terlipressin and norepinephrine, meta-analysis of smaller studies can provide insights needed to understand the comparative effects of these medications. Additionally, recent changes in the HRS diagnosis and treatment guidelines underscore the need for newer analyses comparing terlipressin and norepinephrine. In this systematic review, we aimed to assess reversal of hepatorenal syndrome (HRS) and 1-month mortality in subjects receiving terlipressin or norepinephrine for the management of HRS-AKI. We searched literature databases, including PubMed, Cochrane, Clinicaltrials.gov, International Clinical Trials Registry Platform, Embase, and ResearchGate, for randomized controlled trials (RCTs) published from January 2007 to June 2023 on June 26, 2023. Only trials comparing norepinephrine and albumin with terlipressin and albumin for the treatment of HRS-AKI in adults were included, and trials without HRS reversal as an endpoint or nonresponders were excluded. Pairwise meta-analyses with the random effects model were conducted to estimate odds ratios (ORs) for HRS reversal and 1-month mortality as primary outcomes. Additional outcomes assessed, included HRS recurrence, predictors of response, and incidence of adverse events (AEs). We used the Cochrane risk of bias assessment tool for quality assessment. We included 7 RCTs with a total of 376 subjects with HRS-AKI or HRS type 1. This meta-analysis showed numerically higher rates of HRS reversal (OR 1.33, 95% confidence interval [CI] [0.80-2.22]; P = 0.22) and short-term survival (OR 1.50, 95% CI [0.64-3.53]; P = 0.26) with terlipressin, though these results did not reach statistical significance. Terlipressin was associated with AEs such as abdominal pain and diarrhea, whereas norepinephrine was associated with cardiovascular AEs such as chest pain and ischemia. Most of the AEs were reversible with a reduction in dose or discontinuation of therapy across both arms. Of the terlipressin-treated subjects, 5.3% discontinued therapy due to serious AEs compared to 2.7% of the norepinephrine-treated subjects. Limitations of this analysis included small sample size and study differences in HRS-AKI diagnostic criteria. As more studies using the new HRS-AKI criteria comparing terlipressin and norepinephrine are completed, a clearer understanding of the comparability of these 2 therapies will emerge.

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)0.013
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.029
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0250.038
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.209
GPT teacher head0.384
Teacher spread0.175 · 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 designMeta-analysis
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

Citations12
Published2024
Admission routes1
Has abstractyes

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