Pre-Sepsis Project (PI22/00968) - Plasma proteomic dataset for Identification of Pre-Sepsis using PEA / ELLA-SIMPLEPLEX Technologies

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Authors: Jesús F. Bermejo-Martin
Cited by: 0

Abstract

A total of 180 adult patients were recruited upon admission to the Emergency Departments of Hospital Universitario Río Hortega (Valladolid, Spain) and Complejo Asistencial Universitario de Salamanca (Salamanca, Spain) from March 2023 to November 2024. The inclusion criteria were: (1) age ≥ 18 years, (2) intra-abdominal, urinary, skin and soft tissue, or other non-respiratory infections, and (3) SOFA score ≤ 2 points. Infection was defined according to the US Centers for Disease Control and Prevention National Surveillance Definitions for Specific Types of Infections. Plasma samples were obtained from blood collected in EDTA tubes from all patients within the first 12 hours following admission to the emergency department. Plasma protein concentrations were measured using the antibody-based Olink Explore Proximity Extension Assay (PEA), employing the Explore 3072 panel. A total of 2699 unique proteins were quantified, representing cardiometabolic, inflammatory, neurologic, and oncologic pathways. The data were transformed and normalized to Olink NPX values. NPX is a relative protein quantification unit on a log2 scale. NPX values below the limit of detection (LOD) were replaced with the protein-specific LOD. Dataset SampleID Age: Age (years) Sex: Sex (0=Female; 1=Male) Infection_source: Source of intection (0=Intra-abdominal; 1=Urinary tract; 2: Skin and soft tissue; 3: other) SOFA: Sequential Organ Failure Assessment score NPX: relative protein quantification unit on a log2 scale. Funding: Instituto de Salud Carlos III (ISCIII), PI22/00968, co-funded by the European Union.

Fields of Study & Subjects

Sepsis Diagnosis and Treatment Inflammation biomarkers and pathways Advanced Proteomics Techniques and Applications

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
12 March 2026
Language
EN
Document type
Dataset