Altered albumin/neutrophil to lymphocyte ratio are associated with all-cause and cardiovascular mortality for advanced cardiovascular-kidney-metabolic syndrome

医学 代谢综合征 白蛋白 淋巴细胞 中性粒细胞与淋巴细胞比率 内科学 免疫学 心脏病学 肥胖
作者
Xiaoshuang Yin,Jinmei Zou,Jing Yang
出处
期刊:Frontiers in Nutrition [Frontiers Media]
卷期号:12: 1595119-1595119
标识
DOI:10.3389/fnut.2025.1595119
摘要

Background Advanced cardiovascular-kidney-metabolic (CKM) syndrome refers to stages 3 and 4 of CKM syndrome, which are associated with higher mortality compared to earlier stages (0–2). The albumin (ALB)-to-neutrophil/lymphocyte ratio (ANLR) is a new predictive marker that participates in immune inflammation and dietary status. However, the influence of ANLR on all-cause mortality (ACM) and cardiovascular mortality (CVM) in individuals with advanced CKM syndrome remains unclear. This investigation aims to examine the link between ANLR and both ACM and CVM in this population using data from a large-scale cross-sectional survey in the United States. Methods Data were from the National Health and Nutrition Examination Survey (NHANES) spanning 1999 to 2018, a nationally representative cross-sectional survey with longitudinal mortality follow-up from the National Death Index. The formula of ANLR is ALB/NLR. The diagnostic criteria of CKM syndrome was based on the concept proposed by the American Heart Association and modified criteria adapted for NHANES data availability. The outcomes of interested included ACM and CVM. A 1:1 propensity score matching (PSM) approach was used to control for potential confounding variables. The threshold value of ANLR influencing survival was determined using maximally selected rank statistics, which is based on the log-rank test. This method identifies the optimal cutoff for continuous variables where the difference in survival rates is most pronounced, making it particularly well-suited for analyzing time-to-event data, such as survival outcomes. Kaplan–Meier survival analysis and multivariate Cox proportional hazards models were employed to assess the effects of ANLR on both ACM and CVM. Restricted cubic spline (RCS) analysis evaluated the linear or non-linear association between ANLR and mortality outcomes. Stratified analysis and interaction testing were carried out to estimate the influence of covariates on the ANLR-mortality correlation. Results A total of 3,266 adults with advanced CKM syndrome (41.12% male) were included in the analysis, with median (interquartile range) age of 73 (63–80). Prior to PSM, and fully adjustment, the lowest ANLR Tertile 1 was related to significantly higher risks of ACM (hazard ratio [HR]: 1.58, 95% confidence interval [CI]: 1.39–1.78, p < 0.001) and CVM (HR: 1.65, 95% CI: 1.34–2.04, p < 0.001) compared to the highest Tertile 3. After applying PSM, and fully adjusting for confounders, an ANLR score below 1.04 was independently linked to increased risks of both CVM (HR: 2.02, 95% CI: 1.49–2.75, p < 0.001) and ACM (HR: 1.52, 95% CI: 1.27–1.81, p < 0.001). Interaction tests revealed no significant interactions for CVM across subgroups (All P interaction > 0.05). Regarding ACM, interactions were noted between ANLR and age, gender, and CKM stages (All P interaction < 0.05). RCS analysis indicated an L-shaped link between ANLR and both ACM and CVM, both before and after PSM (all P non-linearity < 0.001). The predictive value of ANLR, NLR, and ALB for CVM and ACM in individuals with advanced CKM syndrome demonstrated that ANLR and NLR exhibited comparable predictive capabilities for both ACM and CVM, outperforming ALB. Furthermore, the predictive performance of ANLR and NLR for ACM was superior to that for CVM. Conclusion Lower ANLR values, indicative of elevated systemic inflammation and malnutrition, are independently linked to increased risks of both ACM and CVM in individuals with advanced CKM syndrome in the US. These readily accessible and low-cost blood markers could serve as valuable prognostic indicators for identifying high-risk individuals. Future research should focus on incorporating additional biomarkers, validating the indices in larger and more diverse cohorts, and employing advanced analytical methods to refine the diagnostic efficiency of ANLR and NLR for better clinical utility.
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