巨细胞性动脉炎的乡村性和延迟诊断——单中心研究。

IF 1.8
Ruoning Ni, Aleksander Lenert, Bharat Kumar
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引用次数: 0

摘要

目的:本研究的目的是比较非农村和农村地区巨细胞动脉炎(GCA)患者的特征,并确定与GCA延迟诊断相关的因素。方法:在这项历史横断面分析中,纳入了符合2022年欧洲风湿病协会联盟/美国风湿病学会GCA分类标准的成年人,并于2000年2月1日至2024年2月7日在爱荷华大学风湿病诊所随访。使用2010年城乡通勤区(RUCA)代码定义地理类别。比较非农村(RUCA 1-3)和农村(RUCA 4-10) GCA患者组的特征。用简单线性回归对GCA诊断的各预测因子和时间进行双变量分析。拟合多变量线性回归模型以确定GCA诊断时间的最佳预测因子。结果:本研究共纳入317例GCA患者(平均年龄72岁;74.8%的女性)。非农村(n = 172)和农村(n = 145)受试者有相似的疾病表现,包括突发性头痛、视力丧失和下颌跛行。与非农村GCA受试者相比,农村GCA诊断的平均时间明显更长(130±185天比45±45天,p < 0.0001)。农村人群的住院率明显更高(24.1%比12.2%,p = 0.0075)。双变量分析确定了与GCA诊断时间相关的4个变量。在多变量线性回归分析中,RUCA代码(β = 13.99, 95%可信区间为9.23 ~ 18.75)、年龄和头痛提供了最佳拟合(调整后R2 = 0.1196, Akaike校正信息标准= 3082,p < 0.001)。结论:乡村性被确定为GCA延迟诊断的最强预测因子。农村患者在接受颞动脉活检方面也有延迟,住院比例较高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rurality and Delayed Diagnosis of Giant Cell Arteritis-A Single-Center Experience.

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.

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