Yin Xiaoshuang, Zou Jinmei, Yang Jing
Department of Immunology, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, Sichuan, China.
Front Med (Lausanne). 2024 Aug 22;11:1446160. doi: 10.3389/fmed.2024.1446160. eCollection 2024.
The investigation purpose was to examine the correlation between the aggregate index of systemic inflammation (AISI) and rheumatoid arthritis (RA) by utilizing the NHANES database from the years 1999 to 2018.
The NHANES database was utilized to extract data spanning from 1999 to 2018. AISI, comprising neutrophils (NEU), monocytes (MONO), platelets (PLT), and lymphocytes (LYM), was computed based on counts. The identification of RA patients was accomplished through questionnaire data. To investigate the connection between AISI and RA, a weighted multivariate regression and subgroup analysis were conducted. In addition, restricted cubic splines (RCS) were employed for examining non-linear associations.
The study encompassed a total of 41,986 patients, among whom 2,642 (6.29%) were diagnosed with RA. Upon controlling for all covariates, the outcomes of the multivariate logistic regression assay demonstrated a statistically significant association between higher Ln(AISI) levels and elevated odds of RA (odds ratio [OR]: 1.097; 95% confidence interval [CI]: 1.096-1.099, < 0.001). The interaction test findings indicate that there is no statistically significant impact within this particular association. The results of the RCS regression model revealed a non-linear pattern in the correlation between Ln(AISI) and RA. The threshold level of AISI for RA was determined as 298.9. The risk of RA rises steeply when AISI surpasses the threshold value.
Overall, a positive association has been observed between AISI and RA. This study highlights the potential of AISI as an innovative, vital, and appropriate inflammatory biomarker for predicting the risk of developing rheumatoid arthritis in older individuals residing in the United States.
本研究旨在利用1999年至2018年的美国国家健康与营养检查调查（NHANES）数据库，探讨全身炎症综合指数（AISI）与类风湿关节炎（RA）之间的相关性。
利用NHANES数据库提取1999年至2018年的数据。根据计数计算包括中性粒细胞（NEU）、单核细胞（MONO）、血小板（PLT）和淋巴细胞（LYM）的AISI。通过问卷数据识别RA患者。为了研究AISI与RA之间的关系，进行了加权多变量回归和亚组分析。此外，采用限制立方样条（RCS）来检验非线性关联。
该研究共纳入41,986名患者，其中2,642名（6.29%）被诊断为RA。在控制所有协变量后，多变量逻辑回归分析结果显示，较高的Ln（AISI）水平与RA患病几率升高之间存在统计学显著关联（比值比[OR]：1.097；95%置信区间[CI]：1.096 - 1.099，P < 0.001）。交互检验结果表明，在这种特定关联中不存在统计学显著影响。RCS回归模型结果显示Ln（AISI）与RA之间的相关性呈非线性模式。RA的AISI阈值水平确定为298.9。当AISI超过阈值时，RA风险急剧上升。
总体而言，观察到AISI与RA之间存在正相关。本研究强调了AISI作为一种创新、重要且合适的炎症生物标志物，对于预测居住在美国的老年人患类风湿关节炎风险的潜力。
