Diagnostic values of different musculoskeletal ultrasound signs, serum uric acid, and their combined detection for gouty arthritis.

ABSTRACT

Objectives: The study aimed to investigate the diagnostic values of different musculoskeletal ultrasound (MSUS) signs, serum uric acid (SUA), and their combined detection for gouty arthritis (GA). Patients and methods: In this retrospective study, 70 patients (62 males, 8 females; mean age 46.1±14.1 years; range, 25 to 86 years) diagnosed with GA (the GA group) between August 2022 and March 2023 and 70 patients (54 females, 16 males; mean age 49.0±14.1 years; range, 21 to 75 years) diagnosed with rheumatoid arthritis and osteoarthritis during the same period (the non-GA group) were included. The positive rate of MSUS signs and SUA in both groups was recorded to compare the differences. The correlations of MSUS signs and SUA with GA were analyzed using Spearman's rank correlation analysis. The diagnostic values of different MSUS signs, SUA, and their combined detection for GA were analyzed using a receiver operating characteristic, the area under the curve (AUC), sensitivity, specificity, and the Youden index. Results: The positive rate of the double contour (DC) sign (chi-squared [χ2 ]=102.935, p<0.001), hyperechoic spots (χ2=56.395, p<0.001), bone erosions (χ2 =10.080, p<0.001), and SUA (χ2 =41.117, p <0.001) were higher in the GA group than in the non-GA group. The positive rate of the DC sign (rs=0.829, p=0.001), hyperechoic spots (rs=0.631, p<0.001), bone erosion (rs=0.268, p=0.001), and SUA (rs=0.542, p<0.001) were positively correlated with GA. Among the single-indicator measures, the DC sign exhibited the highest diagnostic value (AUC=0.907, sensitivity=81.4%, specificity=100%, p<0.001). Among the combined-indicator measures, the DC sign combined with SUA exhibited the highest diagnostic value (AUC=0.929, sensitivity=91.4%, specificity=94.3%, p<0.001), higher than DC sign detection alone. Conclusion: The DC sign combined with SUA yielded a high diagnostic value and can thus provide a reliable basis for effectively and efficiently diagnosing GA.