Article

A circulating proteome-informed prognostic model of COVID-19 disease activity that relies on routinely available clinical laboratories

2022-11-04

Abstract excerpt

A minority of people infected with SARS-CoV-2 will develop severe COVID-19 disease. To help physicians predict who is more likely to require admission to ICU, we conducted an unsupervised stratification of the circulating proteome that identified six endophenotypes (EPs) among 731 SARS-CoV-2 PCR-positive hospitalized participants in the Biobanque Québécoise de la COVID-19, with varying degrees of disease severity...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 7d79733d-2fa0-53f4-a3a8-f92106c526d2
DOI: 10.1101/2022.11.02.22281834

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A circulating proteome-informed prognostic model of COVID-19 disease activity that relies on routinely available clinical laboratoriesDOI 10.1101/2022.11.02.22281834Read

Predicting COVID-19 Patients Outcome Trajectories Using Proteomics and Clinical Biosignatures: A Comprehensive Machine Learning and Bioinformatics ApproachSemantic proximity Read

Circulating proteins to predict adverse COVID-19 outcomesSemantic proximity Read

An immune-protein signature combining TRAIL, IP-10 and CRP for accurate prediction of severe COVID-19 outcomeSemantic proximity Read

Development and validation of blood-based prognostic biomarkers for severity of COVID disease outcome using EpiSwitch 3D genomic regulatory immuno-genetic profilingSemantic proximity Read

A Prognostic Tool for COVID-19 Decision Support: The Intermountain Risk Score Predicts Major Adverse Health Events in Patients Positive for COVID-19Semantic proximity Read

Prognosing the Risk of COVID-19 Death Through a Machine Learning-Based Routine Blood PanelSemantic proximity Read

Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypesSemantic proximity Read

The National COVID Cohort Collaborative: Clinical Characterization and Early Severity PredictionSemantic proximity Read

Distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of COVID-19.Semantic proximity Read

Inflammation Patterns in Omicron Variant-Linked COVID-19: Assessing Biomarkers for Predicting Disease SeveritySemantic proximity Read

Scanning the Medical Phenome to Identify New Medical Diagnoses After Recovery From COVID-19 in a US CohortSemantic proximity Read

A time-resolved proteomic and diagnostic map characterizes COVID-19 disease progression and predicts outcomeSemantic proximity Read