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Rurality and Delayed Diagnosis of Giant Cell Arteritis-A Single-Center Experience
Journal article   Peer reviewed

Rurality and Delayed Diagnosis of Giant Cell Arteritis-A Single-Center Experience

Ruoning Ni, Aleksander Lenert and Bharat Kumar
Journal of clinical rheumatology, Vol.31(8), pp.294-298
12/2025
DOI: 10.1097/RHU.0000000000002267
PMCID: PMC12329242
PMID: 40768558
url
https://pmc.ncbi.nlm.nih.gov/articles/PMC12329242/View
Open Access

Abstract

Objective The study objectives were to compare the characteristics of patients with giant cell arteritis (GCA) from nonrural and rural areas and to identify factors associated with delayed GCA diagnosis. Methods In this historical cross-sectional analysis, adults meeting the 2022 European Alliance of Associations for Rheumatology/American College of Rheumatology GCA classification criteria and followed at the University of Iowa rheumatology clinics from 2/1/2000 to 2/7/2024 were included. Geographic categories were defined using the 2010 Rural-Urban Commuting Area (RUCA) codes. Characteristics of nonrural (RUCA 1–3) and rural (RUCA 4–10) GCA patient groups were compared. Bivariable analyses were performed between each predictor and time to GCA diagnosis with simple linear regression. Multivariable linear regression models were fitted to identify the best predictors of time to GCA diagnosis. Results In total, 317 subjects with GCA were included in this study (mean age, 72 years; 74.8% women). Nonrural (n = 172) and rural (n = 145) subjects had similar disease manifestations, including abrupt headache, vision loss, and jaw claudication. The mean time to GCA diagnosis was significantly longer in rural compared with nonrural GCA subjects (130 ± 185 vs. 45 ± 45 days, p < 0.0001). A significantly higher rate of hospitalizations was observed among rural subjects (24.1% vs. 12.2%, p = 0.0075). Bivariable analyses identified 4 variables associated with time to GCA diagnosis. In multivariable linear regression analyses, RUCA code (β = 13.99, 95% confidence interval, 9.23 to 18.75), age, and headache provided the best fit (adjusted R2 = 0.1196, Akaike corrected information criterion = 3082, p < 0.001). Conclusion Rurality was identified as the strongest predictor of delayed diagnosis in GCA. Rural patients also experienced delays in undergoing temporal artery biopsy and a higher proportion of hospitalizations.
giant cell arteritis diagnosis geographic disparities

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