Xu Qiming, Lin Junyan, Liao Lin, Hu Jing, Lu Jianrao
Institute of Kidney Disease of Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Department of Nephrology, Seventh People's Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China.
PLoS One. 2025 Feb 25;20(2):e0318736. doi: 10.1371/journal.pone.0318736. eCollection 2025.
Albuminuria is a crucial marker of kidney damage and serves as an early indicator of the risk for chronic kidney disease (CKD). Recent studies have suggested that the cardiometabolic index (CMI), could be valuable for screening renal insufficiency. However, the relationship between CMI and albuminuria remains underexplored. Therefore, the aim of this study was to investigate the association between CMI and albuminuria, with the goal of providing new insights for the clinical diagnosis, assessment, and early intervention of kidney disease.
The National Health and Nutrition Examination Survey (NHANES) for the period between 2017-2020 provided the data for this cross-sectional investigation. Triglyceride (TG) (mmol/L)/High density lipid-cholesterol (HDL-C) (mmol/L) × Waist height ratio (WHtR) was the formula used for calculating CMI. Using multifactorial logistic regression, the independent connection between albuminuria and CMI was investigated. The threshold effect was determined by means of a two-stage linear regression model. Additionally, subgroup analysis and interaction tests were carried out.
A total of 3,339 participants were included, and 12.38% of them had albuminuria. As the CMI quartiles grew (quartile 1: 7.78%, quartile 2: 13.43%, quartile 3: 12.93%, quartile 4: 17.01%), so did the probability of albuminuria. The results of adjusted model 3 showed that a greater probability of albuminuria prevalence was strongly correlated with CMI (OR = 2.26, 95% CI: 1.58-3.23). This association held true for all subgroups (all P for trend > 0.05). Furthermore, with a two-stage linear regression model with an inflection point of 0.92, we discovered a nonlinear relationship between CMI and albuminuria.
Our findings indicate that CMI levels are significantly associated with the risk of albuminuria prevalence, suggesting that CMI could serve as a valuable biomarker for assessing the risk of albuminuria.
蛋白尿是肾脏损伤的关键标志物，也是慢性肾脏病（CKD）风险的早期指标。近期研究表明，心脏代谢指数（CMI）可能对筛查肾功能不全具有重要价值。然而，CMI与蛋白尿之间的关系仍未得到充分研究。因此，本研究旨在探讨CMI与蛋白尿之间的关联，为肾脏疾病的临床诊断、评估和早期干预提供新的见解。
2017 - 2020年期间的美国国家健康与营养检查调查（NHANES）为本次横断面研究提供了数据。甘油三酯（TG）（mmol/L）/高密度脂蛋白胆固醇（HDL-C）（mmol/L）×腰围身高比（WHtR）是用于计算CMI的公式。采用多因素逻辑回归分析蛋白尿与CMI之间的独立关联。通过两阶段线性回归模型确定阈值效应。此外，还进行了亚组分析和交互作用检验。
总共纳入了3339名参与者，其中12.38%患有蛋白尿。随着CMI四分位数的增加（四分位数1：7.78%，四分位数2：13.43%，四分位数3：12.93%，四分位数4：17.01%），蛋白尿的发生概率也随之增加。调整模型3的结果显示，蛋白尿患病率的较高概率与CMI密切相关（OR = 2.26，95%CI：1.58 - 3.23）。这种关联在所有亚组中均成立（所有趋势P>0.05）。此外，通过拐点为0.92的两阶段线性回归模型，我们发现CMI与蛋白尿之间存在非线性关系。
我们的研究结果表明，CMI水平与蛋白尿患病率风险显著相关，提示CMI可作为评估蛋白尿风险的有价值生物标志物。
