Evidence map›Paper›PMID 42166469›Full record

ArticlePloS one2026

ADVANTAGE: Advanced discovery of visceral analgesics by neuroimmune targets and the genetics of extreme human phenotype, a study protocol.

Marco Vinicio Alban-Paccha, Nicholas Shenker, Jimena Teran-Perez, Andrew W Horne, George G Malliaras, Christopher Geoffrey Woods, ADVANTAGE Consortium

Abstract read
In one paragraph

Article in PloS one, 2026. 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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Marco Vinicio Alban-PacchaDepartment of Medicine, University of Cambridge, Cambridge, United Kingdom.ORCID https://orcid.org/0000-0003-3948-0446
Nicholas ShenkerDepartment of Medicine, University of Cambridge, Cambridge, United Kingdom.
Jimena Teran-PerezDepartment of Medicine, University of Cambridge, Cambridge, United Kingdom.
Andrew W HorneCentre for Reproductive Health, Institute of Regeneration and Repair, The University of Edinburgh, Edinburgh, United Kingdom.
George G MalliarasElectrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, United Kingdom.
Christopher Geoffrey WoodsDepartment of Medical Genetics, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, United Kingdom.
ADVANTAGE Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chronic visceral pain affects over 20% of adults globally but remains poorly understood, significantly impacting quality of life and healthcare costs. Limited understanding and diagnostic misconceptions hinder effective management, particularly during acute pain flares. This study aims to clarify underlying mechanisms and improve clinical management by combining detailed phenotyping, genetic analysis, immunological profiling, pain mapping, and wearable sensor data in three cohorts: Extreme Visceral Pain, Lack of Visceral Pain, and Healthy Controls. Participants with diverse visceral conditions, such as polycystic kidney disease, inflammatory bowel disease, chronic pancreatitis, endometriosis, painful bladder syndrome, vaginal mesh complications, and fibromyalgia, are recruited via clinical referrals from NHS Cambridge University Hospitals and NHS Lothian. Healthy control volunteers are recruited locally. Data collection involves daily pain ratings captured through a mobile app, wearable physiological monitoring, quantitative sensory testing, detailed medical and lifestyle questionnaires, and bio-sample analyses (genetic variants, autoantibodies). The primary confirmatory outcome evaluates the correlation between wearable sensor parameters and self-reported visceral pain intensity. Genetic analyses, including functional SNP allele discovery and Mendelian gene effect analysis, and immunological profiling will explore underlying biological mechanisms. Challenges anticipated include potential compliance and technical difficulties in remote data collection, potentially affecting data quality. Findings will be disseminated widely, aiming to refine diagnostic tools and inform treatment strategies, ultimately enhancing patient care and outcomes in chronic visceral pain management.

Indexed as

AnalgesicsVisceral PainAdultFemaleHumansMaleMiddle AgedPain MeasurementPhenotypePolymorphism, Single NucleotideAnalgesics

Identifiers

PMID42166469
PMCPMC13193507

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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.