Evidence map›Paper›PMID 39596063›Full record

ArticleInternational journal of molecular sciences2024

Utilising Hyperspectral Autofluorescence Imaging in the Objective Assessment of Disease State and Pain in Patients with Rheumatoid Arthritis.

Florence Lees, Saabah B Mahbub, Martin E Gosnell, Jared M Campbell, Helen Weedon, Abbas Habibalahi, Ewa M Goldys, Mihir D Wechalekar, Mark R Hutchinson, Tania N Crotti

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Article in International journal of molecular sciences, 2024. 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
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0citing papers in PubMed
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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

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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

10 authors.

Florence LeesSchool of Biomedicine, University of Adelaide, Adelaide, SA 5005, Australia.
Saabah B MahbubGraduate School of Biomedical Engineering, University of New South Wales (UNSW), Sydney, NSW 2052, Australia.ORCID 0000-0002-3320-2499
Martin E GosnellQuantitative Pty Ltd., 118 Great Western Highway, Mount Victoria, NSW 2786, Australia.
Jared M CampbellGraduate School of Biomedical Engineering, University of New South Wales (UNSW), Sydney, NSW 2052, Australia.ORCID 0000-0003-0163-4251
Helen WeedonDepartment of Rheumatology, Flinders Medical Centre and Flinders University, Bedford Park, SA 5042, Australia.
Abbas HabibalahiGraduate School of Biomedical Engineering, University of New South Wales (UNSW), Sydney, NSW 2052, Australia.
Ewa M GoldysGraduate School of Biomedical Engineering, University of New South Wales (UNSW), Sydney, NSW 2052, Australia.
Mihir D WechalekarDepartment of Rheumatology, Flinders Medical Centre and Flinders University, Bedford Park, SA 5042, Australia.ORCID 0000-0001-6668-9638
Mark R HutchinsonSchool of Biomedicine, University of Adelaide, Adelaide, SA 5005, Australia.ORCID 0000-0003-2154-5950
Tania N CrottiSchool of Biomedicine, University of Adelaide, Adelaide, SA 5005, Australia.ORCID 0000-0002-5422-3758

Funding

Australian Research Council CE140100003Australian Research Council FT180100565SA Commonwealth scholarship programThe Lincoln CentreUniversity of Adelaide Health and Medical Science Divisional Scholarship
6 · The paper itself

Abstract

Rheumatoid Arthritis (RA) is a chronic inflammatory disease resulting in joint swelling and pain. Treatment options can be reliant on disease activity scores (DAS) incorporating patient global assessments, which are quantified via visual analogue scales (VAS). VAS can be subjective and not necessarily align with clinical symptoms, such as inflammation, resulting in a disconnect between the patient's and practitioners' experience. The development of more objective assessments of pain would enable a more targeted and personalised management of pain within individuals with RA and have the potential to improve the reliability of assessments in research. Using emerging light-based hyperspectral autofluorescence imaging (HAI) technology, we aimed to objectively differentiate disease and pain states based on the analysis of synovial tissue (ST) samples from RA patients. In total, 22 individuals with RA were dichotomised using the DAS in 28-joint counts (DAS-28) into an inactive (IA) or active disease (active-RA) group and then three sub-levels of pain (low, mid, high) based on VAS. HAI was performed on ST sections to identify and quantify the most prominent fluorophores. HAI fluorophore analysis revealed a distinct separation between the IA-RA and active-RA mid-VAS cohort, successfully determining disease state. Additionally, the separation between active-RA Mid-VAS and active RA High-VAS cohort suggests that HAI could be used to objectively separate individuals based on pain severity.

Indexed as

Arthritis, RheumatoidOptical ImagingPainAdultAgedFemaleHumansHyperspectral ImagingMaleMiddle AgedPain MeasurementSeverity of Illness IndexSynovial Membranearthritishyperspectralinflammationrheumatoid

Identifiers

PMID39596063
PMCPMC11593821

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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.