What is the best referral strategy for axial spondyloarthritis? A prospective multicenter study in patients with suspicious chronic low back pain

Ziadé, Nelly; Maroof, Avin; Elzorkany, Bassel; Abdullateef, N.; Adnan, Asal; Abogamal, Ahmed; Saad, Sahar; Kibbi, Lina El; Al-Emadi, Samar; Ansari, A. Al; Najm, Antonella Abi; Younan, Tonine; Kharrat, Khalil; Sebaaly, Amer; Rachkidi, Rami El; Witte, Torsten; Baraliakos, Xenofon

doi:10.1016/j.jbspin.2023.105579

Cited by 3 publications

(1 citation statement)

References 37 publications

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“…Für die Therapie der axSpA empfehlen die Leitlinien eine Kombination aus nichtpharmakologischen und pharmakologischen Optionen 56 , 57 . Die pharmakologische Intervention gliedert sich in drei Stufen ( TAB.…”

Section: Therapie Der Axialen Spondylarthritisunclassified

Hochintensiv gegen Schmerzen – Physiotherapie bei axialer Spondylarthritis

Grenier

2024

physiopraxis

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Menschen mit axialer Spondylarthritis klagen oft über chronisch entzündlich Rückenschmerzen. Gleichzeitig treten Gelenkschwellungen, Sehnen- und Bänderentzündungen auf. Mitunter sind auch Augen, Haut und Darm betroffen. Jean-Pascal Grenier will mehr Bewusstsein für die Anzeichen sowie für therapeutischen Maßnahmen schaffen. Für die Therapie empfehlen sich regelmäßige körperliche Aktivität, intensives Krafttraining, ein gesunder Lebensstil sowie der sofortige Rauch-Stopp.

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Section: Therapie Der Axialen Spondylarthritisunclassified

Hochintensiv gegen Schmerzen – Physiotherapie bei axialer Spondylarthritis

Grenier

2024

physiopraxis

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A scoping review of triage approaches for the referral of patients with suspected inflammatory arthritis, from primary to rheumatology care

Biln,

Bansback,

Shojania

et al. 2024

Rheumatol Int

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Identification of a machine learning-based diagnostic model for axial spondyloarthritis in rheumatological routine care using a random forest approach

Redeker,

Tsiami,

Eicker

et al. 2024

RMD Open

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ObjectivesIn axial spondyloarthritis (axSpA), early diagnosis is crucial, but diagnostic delay remains long and diagnostic criteria do not exist. We aimed to identify a diagnostic model that distinguishes patients with axSpA from patients without axSpA with chronic back pain based on clinical data in routine care.MethodsClinical data from patients with chronic back pain were used, with information on rheumatological examinations based on clinical indications. The total dataset was randomly divided into training and test datasets at a 7:3 ratio. A machine learning-based model was built to distinguish axSpA from non-axSpA using the random forest algorithm. Overall accuracy, sensitivity, specificity and the area under the receiver operating characteristic curve-area under the curve (ROC-AUC) in the test dataset were calculated. The contribution of each variable to the accuracy of the model was assessed.ResultsData from 939 randomly selected patients were available: 659 diagnosed with axSpA and 280 with non-axSpA. In the test dataset, the model reached an accuracy of 0.9234, a sensitivity of 0.9586, a specificity of 0.8438 and a ROC-AUC of 0.9717. Human leucocyte antigen B27 (HLA-B27) contributed most to the accuracy of the model; that is, the accuracy would suffer most from not using HLA-B27, followed by insidious onset of back pain and erosions in the sacroiliac joint.ConclusionsWe provide a machine learning-based model that reveals high performance in diagnosing patients with chronic back pain with axSpA versus without axSpA based on information from a tertiary rheumatology practice. This model has the potential to improve diagnostic delay in patients with axSpA in daily routine settings.

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What is the best referral strategy for axial spondyloarthritis? A prospective multicenter study in patients with suspicious chronic low back pain

Cited by 3 publications

References 37 publications

Hochintensiv gegen Schmerzen – Physiotherapie bei axialer Spondylarthritis

Hochintensiv gegen Schmerzen – Physiotherapie bei axialer Spondylarthritis

A scoping review of triage approaches for the referral of patients with suspected inflammatory arthritis, from primary to rheumatology care

Identification of a machine learning-based diagnostic model for axial spondyloarthritis in rheumatological routine care using a random forest approach

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