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Record W4411431338 · doi:10.1016/j.ard.2025.05.242

OP0231 DEFINING SONOGRAPHIC ENTHESITIS IN PSORIATIC ARTHRITIS: DEVELOPING A DATA- AND EXPERT-DRIVEN DIAGNOSTIC CRITERIA FOR INFLAMMATORY ENTHESITIS AT THE SINGLE ENTHESIS LEVEL

2025· article· en· W4411431338 on OpenAlexaff
André Lucas Ribeiro, Sibel Zehra Aydın, Gurjit S. Kaeley, Fahmeen Afgani, Catherine Bakewell, Marcos Rosemffet, Minna J. Kohler, Amir Haddad, Maria Stoenoiu, Ari Polachek, Josefina Marín, Anne Katz, Sahil Koppikar, Lihi Eder

Bibliographic record

VenueAnnals of the Rheumatic Diseases · 2025
Typearticle
Languageen
FieldMedicine
TopicSpondyloarthritis Studies and Treatments
Canadian institutionsWomen's College HospitalUniversity of TorontoUniversity of Ottawa
Fundersnot available
KeywordsEnthesitisMedicineEnthesisPsoriatic arthritisDermatologySpondyloarthropathyArthritisPsoriasisPathologyImmunology

Abstract

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Background: Enthesitis occurs in 30-40% of psoriatic arthritis (PsA) patients, yet its clinical diagnosis is challenging due to similarities to non-specific entheseal pain. Despite OMERACT's standardization of ultrasound (US) entheseal lesions, a unified definition for inflammatory enthesitis remains vague. These limitations lead to misclassification and, eventually, to overtreatment, underscoring the need for refined diagnostic criteria. Objectives: This study aims to develop data- and expert-driven diagnostic criteria to distinguish inflammatory enthesitis from non-specific sonographic enthesopathy at the single enthesis level. The refinement of diagnostic criteria aims to enhance specificity, thereby reducing overdiagnosis and overtreatment. Methods: An expert panel of 10 sonographers who participated in the Diagnostic Ultrasound Enthesitis Tool (DUET) study reviewed 90 US scans (video clips) of PsA patients representing various severities of entheseal lesions across six sites. Scans were rated on a scale from -10 (definite "No") to +10 (definite "Yes") for the likelihood of enthesitis. Scans rated with ≥ 70% certainty (+7 or higher) by ≥ 70% of readers were classified as "Definite enthesitis". Sonographers also documented the sonographic features influencing their ratings for qualitative analysis. The quantitative analysis used consensus scoring of elementary lesions from the DUET study. Descriptive statistics and Chi-square tests were used to report differences in elementary lesions across categories. Results: Of the 90 scans, 29 (32.2%) were classified as "Definite enthesitis", 21 (23.3%) as "Definite not enthesitis", and 40 (44.5%) had no consensus ("Uncertain"). The likelihood of a scan being classified as inflammatory enthesitis increased with the number of elementary lesions observed (Figure 1A-B). Specifically, 93% of the "Definite enthesitis" scans contained a combination of four or more elementary lesions, whereas the "Uncertain" group primarily displayed between two and four lesions per scan. In contrast, the majority of scans classified as "Definite not enthesitis" exhibited no elementary lesions or isolated findings such as enthesophytes. High-grade Doppler signals near the bone cortex were present in 97% of scans in the "Definite enthesitis" group. However, Doppler was also observed in 55% of "Uncertain" scans, suggesting that its severity and characteristics, including their proximity to the bone cortex and their combination with other elementary lesions, contributed to the diagnostic process. The DUET scoring of elementary lesions and Chi-Square significant differences are shown in Figure 2A-F, highlighting the differences of Hypoechogenicity, Thickening, and Power Doppler between "Definite enthesitis" and "Uncertain" groups. Qualitative analysis highlighted several patterns that were driving the differentiation of inflammatory enthesitis from non-specific enthesopathy. Isolated findings, such as small enthesophytes or minimal hypoechogenicity, were considered by the sonographers as nonspecific and frequently observed in non-inflammatory scenarios. These findings lacked diagnostic certainty unless integrated with other inflammatory or structural features. Structural lesions, such as cortical irregularities and large erosions, while not indicative of active inflammation, were viewed as reflecting prior inflammatory process. Specific Doppler characteristics, such as severity and proximity to bone cortex, in addition to combination with other elementary lesions, were very important for ascertaining a classification of inflammatory enthesitis. Certain enthesis locations, such as the tibial tuberosity and triceps, were more frequently associated with inflammatory enthesitis, especially when multiple structural and inflammatory findings were present. Additionally, the clinical context, including patient characteristics and disease history, was highlighted as essential for accurate interpretation of findings. Conclusion: Inflammatory enthesitis is strongly associated with the presence of ≥ 4 elementary lesions and moderate to high-grade Doppler signal. Isolated lesions lack diagnostic power unless combined with other inflammatory and structural lesions. The clinical context is paramount in classifying an enthesitis as inflammatory or mechanic. These findings, which will inform the development of a standard definition of inflammatory enthesitis for diagnostic purposes in PsA. REFERENCES: [1] Eder L, Aydin S, Kaeley G. The Reliability of Scoring Sonographic Entheseal Abnormalities – the Diagnostic Ultrasound Enthesitis Tool (DUET) Study [abstract]. Arthritis Rheumatol. 2020; 72 (suppl 10). Figure 2The distribution of DUET scores by disease category; 1A. hypoechogenicity (score 0-1); 1B. Enthesophyte (score 0-3); 1C. Thickening (score 0-1); 1D. Calcification (score 0-3); 1E. Erosion (score 0-1); Power Doppler (score 0-3). Chi-Square test was performed to compare the "definite enthesitis" and "uncertain" groups (blue line), with p-value < 0.05 marked with a red asterisk (*) and a p-value < 0.01 marked with two red asterisks (**). Figure 1ANumber of elementary lesions identified in each category; 1B. The distribution of sonographic elementary lesions by category. Acknowledgements: NIL . Disclosure of Interests: Andre Lucas Ribeiro AbbVie and Johnson & Johnson, Sibel Aydin AbbVie, Eli Lilly, Novartis, Pfizer, and UCB, Clarius, AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, Gurjit Kaeley AbbVie, BMS, Gilead, Janssen, Novartis, Fahmeen Afgani: None declared, Catherine Bakewell AbbVie, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, BMS, Eli Lilly, Janssen, Novartis, Pfizer, and UCB, Marcos Rosemffet: None declared, Minna Kohler Springer Publications, Janssen, Novartis, Setpoint Medical, Amir Haddad: None declared, Maria Simona Stoenoiu AbbVie, Janssen, Novartis, Pfizer, Roche, Sanofi, and UCB, AbbVie, Janssen, Novartis, Pfizer, Roche, Sanofi, and UCB, Ari Polachek: None declared, Josefina Marin: None declared, Arnon Katz: None declared, Sahil Koppikar AbbVie, Celltrion, Eli Lilly, Fresenius Kabi, JAMP, Janssen, Novartis, Pfizer, UCB, Sandoz, Lihi Eder Abbvie, UCB, Novartis, Pfizer, J&J, Eli Lilly, BMS, Moonlake, UCB, Novartis, Pfizer, Fresenius Kabi, J&J, Eli Lilly. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.

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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)0.031
metaresearch head score (Gemma)0.071
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.071
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.089
GPT teacher head0.346
Teacher spread0.257 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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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Citations0
Published2025
Admission routes1
Has abstractyes

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