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  • Title: A standardized sonographic analysis of nails in psoriatic arthritis and healthy controls: Feasibility, reliability, diagnostic performance, and demographic and clinical associations.
    Author: Acer Kasman S, Gezer HH, Baklacıoğlu HŞ, Erdem Gürsoy D, Duruöz MT.
    Journal: Joint Bone Spine; 2021 Oct; 88(5):105197. PubMed ID: 33901660.
    Abstract:
    OBJECTIVES: Subunits of the nail can be evaluated by nail ultrasonography (NUSG). The purposes of this study are to document NUSG properties (both nail-based and participant-based evaluations) in patients with psoriatic arthritis (PsA) and healthy controls and to explore the final scorings. METHODS: After the literature review and a pilot study, a consensus was reached to evaluate 12 nails and 5 parameters by NUSG: nail plate impairment (NPI), nail plate thickness (NPT), nail bed thickness (NBT), nail thickness (NT), and Doppler activity (DA); further, scorings for each parameter (NPIs, NPTs, NBTs, NTs, and DAs) were calculated. Group comparisons and diagnostic performances (with ROC curve analysis) were applied to both parameters and scorings. Final scorings to predict PsA diagnosis among the NUSG scorings were reached by regression analysis. Feasibility, reliability, and clinical associations of the scores were also performed. RESULTS: Sixty-four patients with PsA and 26 controls (3240 baseline images) were assessed. The most affected nails, PsA/control comparisons, and the ROC analysis varied among the nails, within the higher values of PsA; therefore, 12 nails remained in the scorings. Participant-based scorings showed better content and diagnostic performances than the nail-based. Diagnostic performances, feasibility, reliability, and regression analysis of the scorings documented that NPIs, NTs, and DAs were the best. Some demographics, employee status, hemoglobin, and disease activity of the participants were associated with them. CONCLUSIONS: The NUSG Index (NUSGI) including NPIs, NTs, and DAs is a feasible, reliable, and discriminative method to predict PsA diagnosis, with its rich content. Clinicaltrials.gov-ID: NCT04718428.
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