30 research outputs found

    Ultrasound definition of tendon damage in patients with rheumatoid arthritis. Results of a OMERACT consensus-based ultrasound score focussing on the diagnostic reliability

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    Methods: We conducted a Delphi study on ultrasounddefined tendon damage and ultrasound scoring system of tendon damage in RA among 35 international rheumatologists with experience in musculoskeletal ultrasound. Twelve patients with RA were included and assessed twice by 12 rheumatologists-sonographers. Ultrasound examination for tendon damage in B mode of five wrist extensor compartments (extensor carpi radialis brevis and longus; extensor pollicis longus; extensor digitorum communis; extensor digiti minimi; extensor carpi ulnaris) and one ankle tendon (tibialis posterior) was performed blindly, independently and bilaterally in each patient. Intraobserver and interobserver reliability were calculated by κ coefficientsRoche Netherlands BV provided funding for the reliability exercise. Roche Netherlands BV did not participate in the study design, data collection, dataanalysis, or writing of the manuscript. Supported by the project (Ministry of Health, Czech Republic) for conceptual development of research organization 023728 (Institute of Rheumatology) and by project No. NT1243

    Sustainability of TNF-blocker tapering in rheumatoid arthritis over 3 years: long-term follow-up of the STRASS (Spacing of TNF-blocker injections in Rheumatoid ArthritiS Study) randomised controlled trial

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    International audienceINTRODUCTION: We have limited data on the sustainability of tumour necrosis factor (TNF)-blocker tapering in rheumatoid arthritis (RA) in remission over the long term in real-life settings. This study aimed to assess the probability of sustained dose reduction of TNF-blockers in an observational 3-year extended follow-up of the Spacing of TNF-blocker injections in Rheumatoid ArthritiS Study (STRASS), a randomised controlled trial comparing progressive TNF-blocker injections (spacing arm (S-arm) to maintenance arm (M-arm)) in patients with RA in stable remission.METHODS: In 2015, clinical data for the completer population were retrospectively collected at 1, 2 and 3 years after the end of the trial. The endpoints were the proportion of patients free of a biological disease-modifying antirheumatic drug (bDMARD) treatment, a sustainably spaced injection of TNF-blockers and a full-dose regimen as well as the mean dose of bDMARD intake and treatment switch rate.RESULTS: Overall, 96 patients (76.8% of the completers) had data available up to 3 years; 11.5% discontinued TNF-blockers (5.8% vs 18.2% in the M-arm and S-arm, p=0.06), 30.2% had a tapered regimen (28.8% vs 31.8%, p=0.76) and 37.5% retained a full dose (44.2% vs 29.5%, p=0.14). The mean TNF-blocker dose quotient was 66% of the full dose (74% vs 58% in the M-arm and S-arm, p=0.06); 20.8% switched to another bDMARD (21.2% vs 20.5%, p=0.94).CONCLUSION: Sustained TNF-blocker de-escalation or withdrawal is achievable in 41% of patients over 3 years with limited dose reduction. Optimal strategies remain to be determined to maintain remission after TNF-blocker tapering or discontinuation

    Detection of flares by decrease in physical activity, collected using wearable activity trackers, in rheumatoid arthritis or axial spondyloarthritis: an application of Machine-Learning analyses in rheumatology

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    International audienceOBJECTIVE:Flares in rheumatoid arthritis (RA) and axial spondyloarthritis (SpA) may influence physical activity. The aim of this study was to assess longitudinally the association between patient-reported flares and activity-tracker-provided steps per minute, using machine learning.METHODS:This prospective observational study (ActConnect) included patients with definite RA or axial SpA. For a 3-month time period, physical activity was assessed continuously by number of steps/minute, using a consumer grade activity tracker, and flares were self-assessed weekly. Machine-learning techniques were applied to the data set. After intrapatient normalization of the physical activity data, multiclass Bayesian methods were used to calculate sensitivities, specificities, and predictive values of the machine-generated models of physical activity in order to predict patient-reported flares.RESULTS:Overall, 155 patients (1,339 weekly flare assessments and 224,952 hours of physical activity assessments) were analyzed. The mean ± SD age for patients with RA (n = 82) was 48.9 ± 12.6 years and was 41.2 ± 10.3 years for those with axial SpA (n = 73). The mean ± SD disease duration was 10.5 ± 8.8 years for patients with RA and 10.8 ± 9.1 years for those with axial SpA. Fourteen patients with RA (17.1%) and 41 patients with axial SpA (56.2%) were male. Disease was well-controlled (Disease Activity Score in 28 joints mean ± SD 2.2 ± 1.2; Bath Ankylosing Spondylitis Disease Activity Index score mean ± SD 3.1 ± 2.0), but flares were frequent (22.7% of all weekly assessments). The model generated by machine learning performed well against patient-reported flares (mean sensitivity 96% [95% confidence interval (95% CI) 94-97%], mean specificity 97% [95% CI 96-97%], mean positive predictive value 91% [95% CI 88-96%], and negative predictive value 99% [95% CI 98-100%]). Sensitivity analyses were confirmatory.CONCLUSION:Although these pilot findings will have to be confirmed, the correct detection of flares by machine-learning processing of activity tracker data provides a framework for future studies of remote-control monitoring of disease activity, with great precision and minimal patient burden

    MRI and serum biomarkers correlate with radiographic features in painful hand osteoarthritis.

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    International audienceTo explore the relationship between clinical findings, biologic biomarkers, conventional radiography and MRI in patients with painful hand OA
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