Associations between pan-immune-inflammation value and abdominal aortic calcification: a cross-sectional study

作者全名："Jin, Chen; Li, Xunjia; Luo, Yuxiao; Zhang, Cheng; Zuo, Deyu"

作者地址："[Jin, Chen; Zhang, Cheng] First Affiliated Hosp Chongqing Med Univ, Dept Cardiothorac Surg, Chongqing, Peoples R China; [Li, Xunjia] Chongqing Hosp Tradit Chinese Med, Dept Nephrol, Chongqing, Peoples R China; [Li, Xunjia; Zuo, Deyu] Chongqing Precis Med Ind Technol Res Inst, Chongqing, Peoples R China; [Luo, Yuxiao] Univ Med Ctr Gottingen, Univ Gottingen, Gottingen, Germany; [Zuo, Deyu] Chongqing Hosp Tradit Chinese Med, Dept Rehabil Med, Chongqing, Peoples R China"

通信作者："Zhang, C (通讯作者)，First Affiliated Hosp Chongqing Med Univ, Dept Cardiothorac Surg, Chongqing, Peoples R China.; Zuo, DY (通讯作者)，Chongqing Precis Med Ind Technol Res Inst, Chongqing, Peoples R China.; Zuo, DY (通讯作者)，Chongqing Hosp Tradit Chinese Med, Dept Rehabil Med, Chongqing, Peoples R China."

来源：FRONTIERS IN IMMUNOLOGY

ESI学科分类：IMMUNOLOGY

WOS号：WOS:001199912300001

JCR分区：Q1

影响因子：5.7

年份：2024

卷号：15

期号：　

开始页：　

结束页：　

文献类型：Article

关键词：abdominal aortic calcification; pan-immune inflammation value; cardiovascular disease; NHANES; inflammation

摘要："Background: Abdominal aortic calcification (AAC) pathogenesis is intricately linked with inflammation. The pan-immune-inflammation value (PIV) emerges as a potential biomarker, offering reflection into systemic inflammatory states and assisting in the prognosis of diverse diseases. This research aimed to explore the association between PIV and AAC. Methods: Employing data from the National Health and Nutrition Examination Survey (NHANES), this cross-sectional analysis harnessed weighted multivariable regression models to ascertain the relationship between PIV and AAC. Trend tests probed the evolving relationship among PIV quartiles and AAC. The study also incorporated subgroup analysis and interaction tests to determine associations within specific subpopulations. Additionally, the least absolute shrinkage and selection operator (LASSO) regression and multivariable logistic regression were used for characteristics selection to construct prediction model. Nomograms were used for visualization. The receiver operator characteristic (ROC) curve, calibration plot and decision curve analysis were applied for evaluate the predictive performance. Results: From the cohort of 3,047 participants, a distinct positive correlation was observed between PIV and AAC. Subsequent to full adjustments, a 100-unit increment in PIV linked to an elevation of 0.055 points in the AAC score (beta=0.055, 95% CI: 0.014-0.095). Categorizing PIV into quartiles revealed an ascending trend: as PIV quartiles increased, AAC scores surged (beta values in Quartile 2, Quartile 3, and Quartile 4: 0.122, 0.437, and 0.658 respectively; P for trend <0.001). Concurrently, a marked rise in SAAC prevalence was noted (OR values for Quartile 2, Quartile 3, and Quartile 4: 1.635, 1.842, and 2.572 respectively; P for trend <0.01). Individuals aged 60 or above and those with a history of diabetes exhibited a heightened association. After characteristic selection, models for predicting AAC and SAAC were constructed respectively. The AUC of AAC model was 0.74 (95%CI=0.71-0.77) and the AUC of SAAC model was 0.84 (95%CI=0.80-0.87). According to the results of calibration plots and DCA, two models showed high accuracy and clinical benefit. Conclusion: The research findings illuminate the potential correlation between elevated PIV and AAC presence. Our models indicate the potential utility of PIV combined with other simple predictors in the assessment and management of individuals with AAC."

基金机构：National Natural Science Foundation of China [82270506]; Natural Science Foundation of Chongqing Science and Technology Committee [CSTB2022NSCQ-MSX0817]; Innovation Fund for Graduate Students of Chongqing Universities [CYB21171]; Project of innovation team for Graduate Teaching [CYYY-YJSJXCX-202318]

基金资助正文："The authors thank the participants in the NHANES study for their contributions and the US Centers for Disease Control and Prevention for their effort to the study design and data organization.r The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by grants from National Natural Science Foundation of China (82270506), Natural Science Foundation of Chongqing Science and Technology Committee (CSTB2022NSCQ-MSX0817), Innovation Fund for Graduate Students of Chongqing Universities (CYB21171) and Project of innovation team for Graduate Teaching (CYYY-YJSJXCX-202318)."