Evidence map›Paper›PMID 38765962›Full record

ArticleResearch square2024

Applying Metabolomics and Aptamer-based Proteomics to Determine Pathophysiologic Differences in Decompensated Cirrhosis Patients Hospitalized with Acute Kidney Injury.

Giuseppe Cullaro, Andrew S Allegretti, Kavish R Patidar, Elizabeth C Verna, Jennifer C Lai

Abstract readPreprint
In one paragraph

Article in Research square, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Giuseppe CullaroUniversity of California-San Francisco.
Andrew S AllegrettiMassachusetts General Hospital.
Kavish R PatidarBaylor College of Medicine and Michael E. DeBakey Veterans Affairs Medical Center.
Elizabeth C VernaColumbia University.
Jennifer C LaiUniversity of California-San Francisco.

Funding

UCSF Liver Core CenterP30DK026743 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Jennifer Y. Chen · 1986 to 2026
$30.7M
The spectrum of cognitive impairment including Alzheimer’s Disease and Related Dementias after liver transplantationR01AG059183 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Jennifer C. Lai · 2018 to 2026
$9.9M
Personalizing Therapies for Acute Kidney Injury in CirrhosisK23DK128567 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · PI Andrew S Allegretti · 2022 to 2026
$982k
Application of Novel Biomarkers of Renal Health in Cirrhosis Patients to Stratify Risk of Acute Kidney Injury Occurrence and ReversibilityK23DK131278 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Giuseppe Cullaro · 2022 to 2026
$812k
The Impact of Frailty on Liver Transplant Outcomes in Older Adults with Hepatocellular CarcinomaK24AG080021 · NIA · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Jennifer C. Lai · 2023 to 2026
$755k
NIA NIH HHS K24 AG080021NIA NIH HHS R01 AG059183NIDDK NIH HHS K23 DK128567NIDDK NIH HHS K23 DK131278NIDDK NIH HHS L30 DK133959NIDDK NIH HHS P30 DK026743
6 · The paper itself

Abstract

A case-control study of 97 patients hospitalized at our institution. We performed aptamer-based proteomics and metabolomics on serum biospecimens obtained within 72 hours of admission. We compared the proteome and metabolome by the AKI phenotype (i.e., HRS-AKI, ATN) and by AKI recovery (decrease in sCr within 0.3 mg/dL of baseline) using ANCOVA analyses adjusting for demographics and clinical characteristics. We completed Random Forest (RF) analyses to identify metabolites and proteins associated with AKI phenotype and recovery. Lasso regression models were developed to highlight metabolites and proteins could improve diagnostic accuracy. Results: ANCOVA analyses showed no metabolomic or proteomic differences by AKI phenotype while identifying differences by AKI recovery status. Our RF and Lasso analyses showed that metabolomics can improve the diagnostic accuracy of both AKI diagnosis and recovery, and aptamer-based proteomics can enhance the diagnostic accuracy of AKI recovery. Discussion: Our analyses provide novel insight into pathophysiologic pathways, highlighting the metabolomic and proteomic similarities between patients with cirrhosis with HRS-AKI and ATN while also identifying differences between those with and without AKI recovery.

Indexed as

Acute Kidney InjuryCirrhosisLiver TransplantMetabolomicsMortalityProteomics

Identifiers

PMID38765962
PMCPMC11100905

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.