Gut August 2019 PMID 31030191

A blood-based prognostic biomarker in IBD.

Daniele Biasci, James C Lee, Nurulamin M Noor, Diana R Pombal, Monica Hou, Nina Lewis, Tariq Ahmad, Ailsa Hart, Miles Parkes, Eoin F McKinney, Paul A Lyons, Kenneth G C Smith

Download social card

Mentions

Peak: 16 in May 2019

across 5 sources since Apr 2019

Extended reach

239,539

potential audience

Total likes

111

Video views

2,867

Mentions per month

Apr 2019 – Aug 2023

Where it's discussed

X / Twitter40 posts
News12 articles
YouTube2 videos
Facebook2 posts
Reddit2 posts

AI synopsis

What people are saying

The discussions demonstrate a high level of excitement about the publication, with many posts describing the study as 'ground-breaking' and pointing out its 'promise' for non-invasive diagnosis and personalized treatment strategies. The tone is enthusiastic and anticipatory, with references to the study’s focus on gene expression and machine learning underpinning a sense of scientific progress and potential clinical impact.

AgreementStrong agreement

The majority of discussions express strong support for the research findings, with phrases like 'ground-breaking work' and 'promising' suggesting enthusiasm and validation from the community.

InterestHigh interest

Posts consistently show high curiosity, highlighting the potential for personalized treatment and non-invasive diagnostics, indicating widespread relevance and engagement with the topic.

EngagementHigh engagement

Numerous posts reference specific details such as gene expression, machine learning, and clinical implications, reflecting deep engagement and analytical interest with the study's methodology and significance.

ImpactHigh impact

Several discussions emphasize the transformative potential of this biomarker for IBD management and personalized medicine, portraying it as a significant advancement in the field.

Abstract in brief

The study identified a blood-based gene expression test that can distinguish between two subgroups of IBD patients (IBD1 and IBD2), which are associated with disease severity, without needing to isolate specific cells.
Using machine learning and qPCR, researchers developed and validated a 17-gene classifier in blood samples that reliably predicts whether a patient will have a more aggressive form of IBD, such as Crohn's disease or ulcerative colitis.
Patients classified as IBDhi (similar to IBD1) tend to experience more severe disease and require earlier treatment escalation, making this biomarker a promising tool for personalized treatment planning in IBD.]

Read the full abstract

All mentions

Blood-Based Biomarker Predicts Disease Severity in Inflammatory Bowel Disease

This study describes a blood-based gene expression test that distinguishes IBD patient subgroups linked to disease severity, using machine learning and qPCR, enabling personalized treatment approaches for Crohn's…

Gastroenterology at BMJ · Sep 26, 2019 2,807 views

Blood-Based Gene Expression Biomarkers for Severity Prediction in IBD

This video discusses a blood-based gene expression test that distinguishes disease severity in IBD patients using a 17-gene classifier. It enables personalized treatment planning by predicting more aggressive disease…

About IBD Podcast · Aug 31, 2023 60 views

Nina

@NinaCPowell · X