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POS0921 INFLUENCE OF HLA-B27 STATUS ON MR IMAGING FINDINGS IN PATIENTS WITH LOW BACK PAIN

2023· article· en· W4379524167 on OpenAlexfundno aff
Sevtap Tugce Ulas, Fabian Proft, Torsten Diekhoff, Valeria Ríos Rodríguez, J. Rademacher, Mikhail Protopopov, Denis Poddubnyy, Katharina Ziegeler

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsnot available
FundersArthritis SocietyNederlandse Organisatie voor Wetenschappelijk OnderzoekDutch Arthritis SocietyGilead SciencesAmgenPfizerEli Lilly and CompanyBristol-Myers SquibbBerlin Institute of HealthGlaxoSmithKline
KeywordsMedicineAnkylosisHLA-B27Sacroiliac jointLow back painBASDAIPopulationEdemaMetaplasiaInternal medicinePathologyPsoriatic arthritisSurgeryArthritisHuman leukocyte antigenImmunologyAntigen

Abstract

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Background The knowledge of factors influencing the susceptibility to and extent of changes at the sacroiliac joints (SIJs) are of great importance in the understanding of pathophysiological processes in axial spondyloarthritis (axSpA)[1]. Recent studies showed that previous delivery and the HLA-B27 status have a special role in the expression of bone marrow edema at the SIJs in the general population. Furthermore, the influence of HLA-B27 differed in men and women[1 2]. Objectives The aim of this study was to investigate the sex-specific influence of the HLA-B27 status on the SIJ lesions such as ankylosis, erosion, fat metaplasia and bone marrow edema and its distribution and extent in patients with low back pain of non-inflammatory origin. Methods In this post-hoc analysis, 139 patients (90 women and 49 men) with low back pain of mechanical/ non-inflammatory origin (after exclusion of axSpA) were included. The MR images of the sacroiliac joints were scored by two trained readers separately for the presence of axSpA features: ankylosis, erosions, sclerosis, fat metaplasia and bone marrow edema. The scoring was performed for the three SIJ regions (ventral/middle/dorsal) differentiated for the sacral and iliac sides. Frequencies of lesions per joint region were compared between HLA-B27 positive and negative individuals using Chi-squared tests. Extent of lesions, expressed as sum scores were compared using T-tests. All analyses were carried out for the entire group and for men and women separately. Results A total of 90 women and 49 men were included in this post-hoc-analysis. HLA-B27 was positive in 33/90 women (36.7%), while this was the case in 23/49 men (46.9%) (further clinical data is given in Table 1). There was no difference in frequency of overall occurrence of erosion (22.9% vs. 16.1%; p = 0.392), sclerosis (48.2% vs. 48.2%; p > 0.999), fat metaplasia (12.0% vs. 7.1%; p = 0.403), bone marrow edema (28.9% vs. 32.1%; p = 0.710) and ankylosis (2.4% vs. 3.6%; p > 0.999) between HLA-B27 negative and positive individuals, respectively. A detailed graphical representation of spatial distribution of lesion within the joint is given in Figure 1. Conclusion In our cohort of pre-selected patients with chronic low back pain and after exclusion of axSpA, the HLA-B27 status did not determine extent or pattern of imaging lesions in either men or women. These results somewhat contradict previously published data on healthy volunteers. This indicates that further studies are needed especially in the investigation of the sex-specific influence of HLA-B27 status on imaging lesions. References [1]Baraliakos X, Richter A, Feldmann D, et al. Which factors are associated with bone marrow oedema suspicious of axial spondyloarthritis as detected by MRI in the sacroiliac joints and the spine in the general population? Ann Rheum Dis 2021;80(4):469-74. doi: 10.1136/annrheumdis-2020-218669 [published Online First: 20201125] [2]Braun J, Baraliakos X, Bulow R, et al. Striking sex differences in magnetic resonance imaging findings in the sacroiliac joints in the population. Arthritis Res Ther 2022;24(1):29. doi: 10.1186/s13075-021-02712-7 [published Online First: 20220120] Acknowledgements: NIL. Disclosure of Interests Sevtap Tugce Ulas Grant/research support from: STU reports funding from the Berlin Institute of Health (BIH) during the conduct of this study (Junior Digital Clinician Scientist Programme)., Fabian Proft Speakers bureau: FP reports grants and personal fees from Novartis, Lilly and UCB, as well as personal fees from AbbVie, AMGEN, BMS, Hexal, Janssen, MSD, Pfizer and Roche., Grant/research support from: FP reports grants and personal fees from Novartis, Lilly and UCB, as well as personal fees from AbbVie, AMGEN, BMS, Hexal, Janssen, MSD, Pfizer and Roche., Torsten Diekhoff Speakers bureau: TD reports personal fees from MSD, Novartis and Eli Lilly., Grant/research support from: TD reports funding from the Berlin Institute of Health (BIH) during the conduct of this study., Valeria Rios Rodriguez Speakers bureau: VRR reports personal fees from AbbVie and Falk e.V., Judith Rademacher Grant/research support from: JR reports funding from the Berlin Institute of Health (BIH) during the conduct of this study (Clinician Scientist Programme)., Mikhail Protopopov Speakers bureau: MP reports personal fees from UCB and Novartis., Denis Poddubnyy Speakers bureau: DP reports personal fees from AbbVie, Eli Lilly, MSD, Novartis, Pfizer, Bristol-Myers Squibb, Roche, UCB, Biocad, GlaxoSmithKline and Gilead outside the submitted work., Grant/research support from: DP reports grants from AbbVie, Eli Lilly, MSD, Novartis, Pfizer and personal fees from Bristol-Myers Squibb, Roche, UCB, Biocad, GlaxoSmithKline and Gilead outside the submitted work., Katharina Ziegeler Grant/research support from: KZ reports funding (research grant) from the Assessment of Spondyloarthritis international Society (ASAS) during the conduct of this study.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.230
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2023
Admission routes1
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