Evidence map›Paper›PMID 40864331›Full record

ArticleAnnals of intensive care2025

Serum proteomes and their prognostic values in sepsis patients admitted to a medical intensive care unit: a single-center study using SWATH-MS proteomics.

Su Yeon Lee, Jee Hwan Ahn, Sang-Bum Hong, Dong-Gon Hyun, Chae-Man Lim, Kyunggon Kim, Jin Won Huh

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Article in Annals of intensive care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Su Yeon LeeDepartment of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea.
Jee Hwan AhnDepartment of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea.
Sang-Bum HongDepartment of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea.
Dong-Gon HyunDepartment of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea.
Chae-Man LimDepartment of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea.
Kyunggon KimDepartment of Convergence Medicine, Asan Medical Center, Asan Institute for Life Sciences, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea. kimkyunggon@gmail.com.
Jin Won HuhDepartment of Pulmonary and Critical Care Medicine, Asan Medical Center, University of Ulsan College of Medicine, 88, Olympic-ro 43-gil, Songpa-gu, Seoul, 05505, South Korea. jwhuh@amc.seoul.kr.ORCID http://orcid.org/0000-0002-3449-0461

Funding

Korea Health Industry Development Institute HR20C0026
6 · The paper itself

Abstract

backgroundRecent developments in proteomics suggest opportunities to understand the pathophysiological heterogeneity of sepsis and provide precision medicine tailored to individual patients. This study aims to evaluate the serum proteomic profiles of patients with sepsis using Sequential Window Acquisition of All Theoretical Mass Spectra proteomics and identify novel biomarkers for assessing sepsis severity and predicting patient outcomes in the ICU.

methodsThis retrospective cohort study included 217 adult patients diagnosed with bacterial sepsis who were admitted to a medical ICU at a single tertiary hospital between January 2011 and January 2020, along with 292 healthy controls. Proteomic analysis was performed to compare patients with sepsis to the 292 healthy controls and analyze differences among sepsis subgroups. The subgroups were classified according to their outcome: early death (within 3 days), late death (after 3 days), and recovery (survived and discharged).

resultsFive key proteins—β-actin (ACTB), fibronectin (FINC), metalloproteinase inhibitor 1 (TIMP1), platelet factor 4 (PF4), and C-X-C motif chemokine 7 (CXCL7)—were identified as significant discriminators of sepsis subgroups with AUCs ranging from 0.786 to 0.833. A six-variable model including 5 proteins and the SOFA score showed the highest AUC value of 0.903 for predicting in-hospital mortality. Multivariable Cox proportional hazards analysis revealed that increased ACTB (hazard ratio [HR] 1.21 [1.07–1.36], p = 0.002), decreased FINC (HR 0.88 [0.79–0.98], p = 0.024), higher SOFA scores (HR 1.08 [1.03–1.13], p = 0.002) and gram-negative sepsis (HR 1.42 [1.02–1.97], p = 0.038) were significantly associated with increased in-hospital mortality.

conclusionsA novel set of biomarkers was identified in this study, including ACTB, FINC, CXCL7, TIMP1, and PF4, for assessing sepsis prognosis. The six-variable model incorporating SOFA scores demonstrated a high prognostic value for in-hospital mortality, potentially enabling more accurate risk stratification for patients with sepsis in the ICU.

Indexed as

BiomarkersIntensive care unitsPrognosisProteomicsSepsis

Identifiers

PMID40864331
PMCPMC12391578

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