{"title":"Association between the aggregate index of systemic inflammation and CKD: evidence from NHANES 1999-2018.","authors":"Dongli Huang, Hang Wu","doi":"10.3389/fmed.2025.1506575","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>We aimed to investigate the potential association between the aggregate index of systemic inflammation (AISI) and chronic kidney disease (CKD).</p><p><strong>Patients and methods: </strong>This study analyzed data from the National Health and Nutrition Examination Survey (NHANES) spanning 1999 to 2018. CKD was defined as either an estimated glomerular filtration rate (eGFR) of less than 60 mL/min/1.73 m<sup>2</sup> or the presence of albuminuria, defined as a urine albumin-to-creatinine ratio (ACR) of 30 mg/g or higher. Low eGFR is an eGFR of less than 60 mL/min/1.73 m<sup>2</sup>. Multivariate regression analysis, smoothed curve fitting, and subgroup analyses were conducted to investigate the relationship between the Inflammatory status index (AISI) and CKD. The receiver operating characteristic (ROC) curve analysis was used to evaluate its ability to identify CKD and low eGFR. The AISI was transformed using the natural logarithm (Ln) for statistical analysis.</p><p><strong>Results: </strong>Of the 50,768 recruits, 49.86% were male. The prevalence of CKD and low eGFR was 20.31% and 8.57%, respectively. Ln-AISI was positively associated with CKD (OR = 1.24; 95% CI: 1.19, 1.28) and low eGFR (OR = 1.17; 95% CI:1.11, 1.24). Smooth curve fitting revealed a positive association between AISI and CKD and low eGFR. Subgroup analysis and interaction tests indicated that stratifications did not significantly alter the association between AISI and CKD and low eGFR. Threshold effect analysis indicated that this relationship became more pronounced when Ln-AISI exceeded 5.2 (AISI > 181.27). The ROC analysis showed that AISI had better discrimination and accuracy for identifying CKD and low eGFR compared to other inflammatory indicators [lymphocyte count (LYM), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR), and the product of platelet count and neutrophil count (PPN)].</p><p><strong>Conclusion: </strong>AISI was significantly and positively correlated with the prevalence of CKD, and this relationship was more potent when AISI was greater than 181.27. Compared with other inflammatory indicators, AISI was more effective in identifying CKD.</p>","PeriodicalId":12488,"journal":{"name":"Frontiers in Medicine","volume":"12 ","pages":"1506575"},"PeriodicalIF":3.1000,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11931135/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fmed.2025.1506575","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: We aimed to investigate the potential association between the aggregate index of systemic inflammation (AISI) and chronic kidney disease (CKD).
Patients and methods: This study analyzed data from the National Health and Nutrition Examination Survey (NHANES) spanning 1999 to 2018. CKD was defined as either an estimated glomerular filtration rate (eGFR) of less than 60 mL/min/1.73 m2 or the presence of albuminuria, defined as a urine albumin-to-creatinine ratio (ACR) of 30 mg/g or higher. Low eGFR is an eGFR of less than 60 mL/min/1.73 m2. Multivariate regression analysis, smoothed curve fitting, and subgroup analyses were conducted to investigate the relationship between the Inflammatory status index (AISI) and CKD. The receiver operating characteristic (ROC) curve analysis was used to evaluate its ability to identify CKD and low eGFR. The AISI was transformed using the natural logarithm (Ln) for statistical analysis.
Results: Of the 50,768 recruits, 49.86% were male. The prevalence of CKD and low eGFR was 20.31% and 8.57%, respectively. Ln-AISI was positively associated with CKD (OR = 1.24; 95% CI: 1.19, 1.28) and low eGFR (OR = 1.17; 95% CI:1.11, 1.24). Smooth curve fitting revealed a positive association between AISI and CKD and low eGFR. Subgroup analysis and interaction tests indicated that stratifications did not significantly alter the association between AISI and CKD and low eGFR. Threshold effect analysis indicated that this relationship became more pronounced when Ln-AISI exceeded 5.2 (AISI > 181.27). The ROC analysis showed that AISI had better discrimination and accuracy for identifying CKD and low eGFR compared to other inflammatory indicators [lymphocyte count (LYM), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR), and the product of platelet count and neutrophil count (PPN)].
Conclusion: AISI was significantly and positively correlated with the prevalence of CKD, and this relationship was more potent when AISI was greater than 181.27. Compared with other inflammatory indicators, AISI was more effective in identifying CKD.
期刊介绍:
Frontiers in Medicine publishes rigorously peer-reviewed research linking basic research to clinical practice and patient care, as well as translating scientific advances into new therapies and diagnostic tools. Led by an outstanding Editorial Board of international experts, this multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide.
In addition to papers that provide a link between basic research and clinical practice, a particular emphasis is given to studies that are directly relevant to patient care. In this spirit, the journal publishes the latest research results and medical knowledge that facilitate the translation of scientific advances into new therapies or diagnostic tools. The full listing of the Specialty Sections represented by Frontiers in Medicine is as listed below. As well as the established medical disciplines, Frontiers in Medicine is launching new sections that together will facilitate
- the use of patient-reported outcomes under real world conditions
- the exploitation of big data and the use of novel information and communication tools in the assessment of new medicines
- the scientific bases for guidelines and decisions from regulatory authorities
- access to medicinal products and medical devices worldwide
- addressing the grand health challenges around the world