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Enregistrement W4411429142 · doi:10.1016/j.ard.2025.05.519

POS0131 DEVELOPMENT AND VALIDATION OF A TIME-EFFICIENT SIMPLIFIED SPARCC MRI SCORE IN AXIAL SPONDYLOARTHRITIS

2025· article· en· W4411429142 sur OpenAlexaboutno aff
Fatma Abdelrahman, Mohamed Mortada, Hassan Abdelwahab, E.S.A.H.F. El-Sayyad, Mohammad Abd Alkhalik Basha

Notice bibliographique

RevueAnnals of the Rheumatic Diseases · 2025
Typearticle
Langueen
DomaineMedicine
ThématiqueSpondyloarthritis Studies and Treatments
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineAxial spondyloarthritisNuclear medicineInternal medicineAnkylosing spondylitisSacroiliitis

Résumé

récupéré en direct d'OpenAlex

Background: Axial spondyloarthritis (axSpA) is a chronic inflammatory condition that primarily affects the spine and sacroiliac joints (SIJs), leading to significant suffering. It falls under the broader category of spondyloarthritis, which presents a considerable diagnostic challenge owing to nonspecific symptoms and a notable lack of radiographic evidence in the early stages of the disease [1]. Magnetic resonance imaging (MRI) has become an indispensable diagnostic tool for evaluating axSpA that can detect both active inflammation and structural changes in the SIJs and spine. It is the standard imaging modality recommended for the assessment of axSpA, as supported by the ankylosing spondylitis Working Group of the International Association for the Assessment of Spine Arthritis (ASAS) and Outcome Measures in Rheumatoid Arthritis Clinical Trials (OMERACT) [2]. Various MRI scoring systems are in use, with the Spondyloarthritis Research Consortium of Canada (SPARCC) score being notably sensitive in detecting subtle changes in inflammation and correlating positively with clinical measures of disease activity [3]. Despite advancements in the management of axSpA, the absence of standardized methods for routinely assessing disease activity remains a significant challenge. The current SPARCC MRI score, although valuable, is time-consuming and depending on individual conditions. Objectives: To develop and validate a simplified SPARCC score for detecting disease activity in patients with axSpA and compare its performance with the original SPARCC score. Methods: This prospective study included 60 patients with axSpA diagnosed according to the ASAS classification criteria who were naïve to biologic DMARDs. Disease activity and physical function in axSpA patients were assessed using several indices at baseline and six months after biological therapy. Improvement was defined as either an ASDAS-Clinically Important Improvement (ASDAS-CII) (a decrease of ≥ 1.1) or ASDAS-Major Improvement (ASDAS-MI) (a decrease of ≥ 2.0). MRI examinations of SIJs and spine were performed at baseline and six months after biological therapy. The simplified SPARCC score, focusing on the three most affected slices/vertebrae instead of six, was developed and compared with the original SPARCC score. Both original and simplified SPARCC scores were correlated with clinical indices and inflammatory markers (CRP and ESR). Inter-reader agreement and diagnostic performance were evaluated to assess reliability and clinical utility. Results: The study included 60 axSpA patients with mean age of 29.78 years, with male predominance (68.3%). Median disease duration was 4 years (0.5-10). 45% of the patients had peripheral arthritis, 15% had psoriasis, 5% had inflammatory bowel disease and 3.3% had uveitis. HLA-B27 was positive in 43.3%. By comparing various disease activity markers and clinical scales at baseline and 6 months post-therapy; all parameters showed significant improvement (p<0.001) (median ESR decreased from 35.0 to 12.0, CRP from 17.5 to 2.0, BASDAI from 7.0 to 2.0, BASFI from 6.0 to 2.0, and BASMI from 4.0 to 2.0). Mean ASDAS-CRP decreased from 4.02 to 1.91 with 38.3% achieved inactive status. Both the original and simplified SPARCC scores showed significant improvement after six months of biological therapy (p<0.001). The simplified SPARCC scores demonstrated strong correlations with disease activity markers, comparable to or stronger than the original scores. BASDAI and ASDAS showed strong correlations with both systems. BASDAI correlated with original (r=0.421) and simple (r=0.413) scores at baseline. ASDAS correlated with original (r=0.419) and total scores (r=0.425). Simplified SPARCC total scores had the best diagnostic accuracy for detecting the disease activity (AUC 0.810, sensitivity 76.3%, specificity 66.7% at cut-off 9.0). Original SPARCC SIJ and total scores performed similarly (AUC 0.794, sensitivity 75%, specificity 82.7% at cut-offs 12.0 and 24.0). Spine scores showed high sensitivities (87.5-89.5%) but lower specificities (67.3%). Inter-reader agreement was substantial to almost perfect for all scores, with simplified SPARCC spine score exhibiting highest agreement (κ= 0.817 at baseline and 0.784 at follow-up) followed by simple total scores (k=0.716 baseline, k=0.744 follow-up). The simplified scoring significantly reduced assessment time (Figure 1): SIJ scoring from 16.9 ± 2.5 to 6.2 ± 1.9 minutes, spine from 14.8 ± 2.4 to 5.6 ± 1.4 minutes, and total from 37.1 ± 9.2 to 10.7 ± 2.9 minutes (all p<0.001). Figure 1 Conclusion: This study supports the construct validity of the simplified SPARCC MRI score in assessing inflammation in patients with axSpA.The application of this new score has advantages of improved inter-reader reliability and significantly reduced assessment time. REFERENCES: [1] Bittar M, Khan MA, Magrey M (2023) Axial Spondyloarthritis and Diagnostic Challenges: Over-diagnosis, Misdiagnosis, and Under-diagnosis. Curr Rheumatol Rep 25:47-55. [2] Khmelinskii N, Regel A, Baraliakos X (2018) The Role of Imaging in Diagnosing Axial Spondyloarthritis. Front Med 5:106. [3] Maksymowych WP, Wichuk S, Dougados M et al (2017) MRI evidence of structural changes in the sacroiliac joints of patients with non-radiographic axial spondyloarthritis even in the absence of MRI inflammation. Arthritis Res Ther 19:126. Table 1VariablesBaseline (n=60)Follow-up (n=60)% of improvementP-valueOriginal SPARCC SIJ22 (21.3), 4 – 566 (10.5), 0 – 2373.8<0.001Simple SPARCC SIJ19 (20.5), 4 – 366 (9.25), 0 – 2171.4<0.001Original SPARCC spine13 (16.3), 0 – 511.5 (10), 0 – 2278.8<0.001Simple SPARCC spine11.5 (15.25), 0 – 471.5 (8), 0 – 1879<0.001Original SPARCC total36.5 (36.5), 5 – 1016 (17), 0 – 4575.5<0.001Simple SPARCC total21 (25), 0 – 693 (16), 0 – 3079.1<0.001 Acknowledgements: NIL . Disclosure of Interests: None declared . © 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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,009
score de la tête « metaresearch » (Gemma)0,013
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Méthodes · Signal consensuel: aucune
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,049

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0090,013
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,001
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0050,003

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,026
Tête enseignante GPT0,294
Écart entre enseignants0,267 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreMéthodes

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2025
Routes d'admission1
Résumé présentoui

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