University of California, San Francisco.
Arthritis Care Res (Hoboken). 2023 Oct;75(10):2073-2081. doi: 10.1002/acr.25121. Epub 2023 Apr 27.
Health disparities in adult lupus, including higher disease severity and activity among those in poverty, have been identified. Similar associations in pediatric lupus have not been clearly established. This study was undertaken to investigate the relationship of income level and other socioeconomic factors with length of stay (LOS) in the hospital and severe lupus features using the 2016 Kids' Inpatient Database (KID).
Lupus hospitalizations were identified in children ages 2-20 years in the 2016 KID using International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) codes (M32). Univariate and multivariate negative binomial regression analyses were used to analyze the association of income level, race and ethnicity, and insurance status with LOS in the hospital. Univariate and multivariate logistic regression analyses were used to analyze the association of the same predictors with the presence of severe lupus features, defined using ICD-10 codes associated with lupus sequelae (e.g., lupus nephritis).
A total of 3,367 unweighted (4,650 weighted) lupus hospitalizations were identified. Income level was found to be a statistically significant predictor of increased LOS in the hospital for those in the lowest income quartile (adjusted incidence rate ratio 1.12 [95% confidence interval (95% CI) 1.02-1.23]). Black race, "other" race, and public insurance were also associated with severe lupus features (adjusted odds ratio [OR ] 1.51 [95% CI 1.11-2.06]; OR 1.61 [95% CI 1.01-2.55]; and OR 1.51 [95% CI 1.17-2.55], respectively).
Using a nationally representative data set, income level was found to be a statistically significant predictor of LOS in the hospital among those with the lowest reported income, highlighting a potential target population for intervention. Additionally, Black race and public insurance were associated with severe lupus features.
已确定成人狼疮中存在健康差异,包括贫困人群的疾病严重程度和活动度更高。但在儿科狼疮中,尚未明确存在类似的关联。本研究旨在使用 2016 年儿童住院数据库(KID)调查收入水平和其他社会经济因素与住院时间(LOS)和严重狼疮特征的关系。
使用国际疾病分类和相关健康问题第十次修订版(ICD-10)代码(M32)在 2016 年 KID 中识别 2-20 岁儿童的狼疮住院患者。使用单变量和多变量负二项式回归分析来分析收入水平、种族和民族以及保险状况与住院 LOS 的关系。使用单变量和多变量逻辑回归分析来分析相同预测因子与严重狼疮特征存在的关系,这些特征使用与狼疮后遗症相关的 ICD-10 代码(例如狼疮肾炎)来定义。
共确定了 3367 例未加权(4650 例加权)狼疮住院患者。对于收入最低四分位数的患者,收入水平是住院 LOS 增加的统计学显著预测因素(调整后的发病率比 1.12[95%置信区间(95%CI)1.02-1.23])。黑人、“其他”种族和公共保险也与严重狼疮特征相关(调整后的比值比[OR]1.51[95%CI 1.11-2.06];OR 1.61[95%CI 1.01-2.55];和 OR 1.51[95%CI 1.17-2.55])。
使用全国代表性数据集,发现收入最低报告收入的患者住院 LOS 是统计学显著的预测因素,突出了一个潜在的干预目标人群。此外,黑人种族和公共保险与严重狼疮特征相关。